• YOLO Object Detection

    You Only Look Once - this object detection algorithm is currently the state of the art, outperforming R-CNN and it's variants. I'll go into some different object detection algorithm improvements over the years, then dive into YOLO theory and a programmatic implementation using Tensorflow! Code for this video: https://github.com/llSourcell/YOLO_Object_Detection Please Subscribe! And like. And comment. That's what keeps me going. Want more inspiration & education? Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology More learning resources: https://pjreddie.com/darknet/yolo/ https://timebutt.github.io/static/how-to-train-yolov2-to-detect-custom-objects/ http://machinethink.net/blog/object-detection-with-yolo/ https://github.com/pjreddie/darkne...

    published: 15 Nov 2017
  • How computers learn to recognize objects instantly | Joseph Redmon

    Ten years ago, researchers thought that getting a computer to tell the difference between a cat and a dog would be almost impossible. Today, computer vision systems do it with greater than 99 percent accuracy. How? Joseph Redmon works on the YOLO (You Only Look Once) system, an open-source method of object detection that can identify objects in images and video -- from zebras to stop signs -- with lightning-quick speed. In a remarkable live demo, Redmon shows off this important step forward for applications like self-driving cars, robotics and even cancer detection. Check out more TED talks: http://www.ted.com The TED Talks channel features the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes (or ...

    published: 18 Aug 2017
  • Computer Vision with MATLAB for Object Detection and Tracking

    Download a trial: https://goo.gl/PSa78r See what's new in the latest release of MATLAB and Simulink: https://goo.gl/3MdQK1 Computer vision uses images and video to detect, classify, and track objects or events in order to understand a real-world scene. In this webinar, we dive deeper into the topic of object detection and tracking. Through product demonstrations, you will see how to: Recognize objects using SURF features Detect faces and upright people with algorithms such as Viola-Jones Track single objects with the Kanade-Lucas-Tomasi (KLT) point tracking algorithm Perform Kalman Filtering to predict the location of a moving object Implement a motion-based multiple object tracking system This webinar assumes some experience with MATLAB and Image Processing Toolbox. We will focus on th...

    published: 28 Apr 2017
  • How To Detect Objects with a CLICK PLC

    http://www.AutomationDirect.com/click-plc (VID-CL-0022) - Learn how to connect any PNP or NPN proximity, photo electric or ultrasonic sensor and mechanical switches to a CLICK PLC for object sensing and detection. To learn more visit http://www.automationdirect.com/click-plc To SUBSCRIBE: http://www.youtube.com/subscription_center?add_user=automationdirect Facebook: http://www.AutomationDirect.com/Facebook Twitter: http://www.AutomationDirect.com/Twitter Google: http://www.AutomationDirect.com/google-plus Related AutomationDirect.com part numbers: C0-00DD1-D, C0-00DD2-D, C0-00DR-D, C0-00AR-D, C0-01DD1-D, C0-01DD2-D, C0-01DR-D, C0-01AR-D, C0-02DD1-D, C0-02DD2-D, C0-02DR-D, C0-10DD1E-D, C0-10DD2E-D, C0-10DRE-D, C0-10DRE-D, C0-11DD1E-D, C0-11DD2E-D, C0-11DRE-D, C0-11ARE-D, C0-12DD1E-D, ...

    published: 04 May 2015
  • Object Detection and Recogition

    http://www.willowgarage.com/blog/2010/09/20/scalable-object-recognition

    published: 31 Aug 2010
  • Matlab object tracking using webcam tutorial Matlab ( detect red )

    A complete tutorial with source code explained using live video feed from webcam and track red colored objects. We use image acquisition tool box. For more tutorials and matlabcode Visit: http://www.solved4u.weebly.com

    published: 07 Mar 2015
  • How To Detect Objects with a Productivity Series Controller

    http://www.AutomationDirect.com//p2000 (VID-P2-0003) - Learn how to connect any PNP or NPN proximity, photo electric or ultrasonic sensor and mechanical switches to a Productivity Series controller for object sensing and detection. A Productivity 2000 controller is used in this video, but is also applicable to the Productivity 3000. To learn more visit http://www.automationdirect.com//p2000 To SUBSCRIBE: http://www.youtube.com/subscription_center?add_user=automationdirect Facebook: http://www.AutomationDirect.com/Facebook Twitter: http://www.AutomationDirect.com/Twitter Google: http://www.AutomationDirect.com/google-plus Related AutomationDirect.com part numbers: P1-540, P1-START, MICSD-16G, P1-01AC, P1-08ND3, P1-08TD1, P1-08TD2, P1-15CDD1, P1-15CDD2, P1-16CDR, P1-08TRS, P1-16TR, P1...

    published: 04 May 2015
  • Object detection with Tensorflow - Self Driving Cars p.17

    Hello and welcome to another Python and self-driving cars tutorial. In this tutorial, we're going to cover the implementation of the TensorFlow Object Detection API into the realistic simulation environment that is GTAV. Due to the realistic representations that occur inside of GTAV, we can use object detectors that were made for the real-world, and still see success. For example, we can detect cars, people, stop signs, trucks, and stop lights. Text tutorials and sample code: https://pythonprogramming.net/tensorflow-object-detection-api-self-driving-car/ https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex

    published: 04 Sep 2017
  • How to Detect Color Objects with OpenCV C++

    Please visit us at http://opencv-srf.blogspot.com/2010/09/object-detection-using-color-seperation.html for more information on how to detect color objects with OpenCV/C++

    published: 19 Apr 2014
  • Basic EV3 program to Detect and Push objects

    Basic EV3 program to Detect and Push objects

    published: 21 Apr 2016
  • Bosch Universal Detector D-Tect 120 [Detect Live Cables, Metal, Wooden Object, Water Pipes]

    The most convenient universal detector for reliable detection of all materials including plastic Product Features - Innovative center finder technology gives direction indication for precise location of object center - Spot measurement enables you to perform measurement with great ease - Reliable detection of all objects with an easy user interface featuring 3 mode buttons Purchase Link : http://hardwarespecialist.com.sg/product/bosch-professional-d-tect-120/ Retail Address: 10 Kaki Bukit Road 2 #01-02 First East Centre Singapore 417868

    published: 25 Jan 2017
  • How to Detect an Object with Robotiq Grippers

    http://robotiq.com/products/ This video will explain you how to detect an object with Robotiq Grippers. If you want to know more about object detection with the Robotiq Grippers, look at the online instruction manual available at http://support.roboptiq.com.

    published: 16 May 2016
  • Chinese Street surveillance. Object / Face Recognition.

    Part of the "sense" line of real time video analysis. Click Here To Subscribe! ►https://www.youtube.com/channel/UCseFtoNUVuegUgM3s60sE4A?sub_confirmation=1 Twitter ► https://twitter.com/ID_R_McGregor

    published: 23 Sep 2017
  • How To Detect Objects with a Do-more PLC

    http://www.AutomationDirect.com/Do-more-PLCs (VID-DM-0023) - Learn how to connect any PNP or NPN proximity, photo electric or ultrasonic sensor and mechanical switches to a Do-more PLC for object sensing and detection. A Do-more H2-DM1E is used in this video, but is also applicable to the T1H-DM1x Terminator PLCs. To learn more visit http://www.automationdirect.com/Do-more-PLCs To SUBSCRIBE: http://www.youtube.com/subscription_center?add_user=automationdirect Facebook: http://www.AutomationDirect.com/Facebook Twitter: http://www.AutomationDirect.com/Twitter Google: http://www.AutomationDirect.com/google-plus Related AutomationDirect.com part numbers: BX-DM1E-M-D, BX-DM1E-M, BX-DM1-10AR-D, BX-DM1-10ER-D, BX-DM1-10ED1-D, BX-DM1-10ED2-D, BX-DM1E-10AR3-D, BX-DM1E-10ER3-D, BX-DM1E-10ED13-D...

    published: 04 May 2015
  • MIT’s “CornerCameras” system can detect objects or people in a Hidden Scene

    MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers have developed a new system named as “CornerCameras”, to detect objects or people in a hidden scene and measure their speed and trajectory — all in real-time. This “CornerCameras” system can work with smartphone cameras to see things hidden around corners. To explain, imagine that you’re walking down an L-shaped hallway and have a wall between you and some objects around the corner. Those objects reflect a small amount of light on the ground in your line of sight, creating a fuzzy shadow that is referred to as the “penumbra.” Using video of the penumbra, the system can stitch together a series of one-dimensional images that reveal information about the objects around the corner. The team was surpr...

    published: 10 Oct 2017
  • detect objects

    published: 14 Feb 2017
  • 26 - How to Detect Mouse Click or Touch on a GameObject

    In this video you will learn how to detect a mouse click or tap on a gameobject with the help of ray and raycast. Download Code : https://drive.google.com/open?id=0B__1zp7jwQOKT1NiamoyMFlDaVE

    published: 05 Feb 2017
  • Introduction to CoreML: Detect Dominant Object on an Image (Swift 4 & XCode 9)

    In this video, we will go through an introduction on CoreML detecting the dominant object in an image. Project: http://bit.ly/2xOgswO Follow Me: Twitter: https://twitter.com/VasilNunev Instagram: https://instagram.com/v.nunev iTunes: https://itunes.apple.com/us/developer/vasil-nunev/id1263932026

    published: 19 Sep 2017
  • Detect object name and meaning

    Find out the name and meaning of objects by taking a photo of them. Ability to take a photo of one specific object which user does not the meaning of that. The camera would detect the object name by the power of machine learning and then the definition and meaning and example for this object would be shown to the user automatically and then save them on the device. App in iTunes: https://itunes.apple.com/us/app/ielts-speaking-master/id1329270990?mt=8

    published: 08 Feb 2018
  • River Treasure! - Iphone 6, Camera, Rings, Knives and More!

    What an Amazing Adventure out on the river! I found lots of awesome things with my AT Pro, while searching for my friend's lost wedding ring. After 10 hours of Metal Detecting I recovered many rings, one is a 14K Gold wedding band, but it is not the one I was looking for. Joe's ring is still somewhere in the river, next time we may find it. My best finds from this trip are the Iphone 6 (Which I had returned to the owner), The Rings, Waterproof Lumix Camera and the nice shades. Link to the metal detector I use: https://www.battleground-detectors.com/shop/garrett-metal-detectors/94-garrett-at-pro-pro-pointer-at.html This video was filmed with my Olympus camera. Here's the link http://amzn.to/2ki8HIG , these camera are rugged! I will have more videos of detecting in the river coming soon!...

    published: 27 Jul 2016
  • Unity3D How to : Detect Mouse Click on an Object

    This is how to check if there's a mouse click on n object attached with collider(or collider2D) and then do anything you want :) If you think this tutorial is useful, don't forget to like - share - subscribe. And here is my game for Android https://play.google.com/store/apps/details?id=com.tawan.kiu

    published: 21 Oct 2014
  • Lecture 11 | Detection and Segmentation

    In Lecture 11 we move beyond image classification, and show how convolutional networks can be applied to other core computer vision tasks. We show how fully convolutional networks equipped with downsampling and upsampling layers can be used for semantic segmentation, and how multitask losses can be used for localization and pose estimation. We discuss a number of methods for object detection, including the region-based R-CNN family of methods and single-shot methods like SSD and YOLO. Finally we show how ideas from semantic segmentation and object detection can be combined to perform instance segmentation. Keywords: Semantic segmentation, fully convolutional networks, unpooling, transpose convolution, localization, multitask losses, pose estimation, object detection, sliding window, regio...

    published: 11 Aug 2017
  • Russia: These devices could help special forces detect enemies through walls

    Russia's Logis-Geotech demonstrated two detection devices which the company says are capable of detecting objects and people through thick concrete walls, in Moscow on Friday. The firm says the detectors could be critical in combat operations. The radars are said to be extremely sensitive and can detect a person breathing even if he remains still and does not move at all. Andrei Padenko, Representative of Logis-Geotech Group (Russian): "[We are presenting] two devices. RO-400 is a stationary device that is mounted against a wall and has the maximum range of detection. It can detect [signals] through 60 centimetre (23 inch)-thick concrete walls and even through two walls. The RO-900 is a portable device. Its [total] range of detection is a bit lower, up to 11 meters (36 feet), and it can ...

    published: 18 Nov 2016
  • Schauenburg : dotNetix - Using Deep Neural Networks to detect objects in a road scene.

    Schauenburg/dotNetix develops collision avoidance systems. This is a demonstrator of how our Deep Neural Network implimentation to detect vehicles and people. The driver of the vehicle is warned of a potential collision with the object.

    published: 23 Jan 2018
developed with YouTube
YOLO Object Detection
21:51

YOLO Object Detection

  • Order:
  • Duration: 21:51
  • Updated: 15 Nov 2017
  • views: 262482
videos
You Only Look Once - this object detection algorithm is currently the state of the art, outperforming R-CNN and it's variants. I'll go into some different object detection algorithm improvements over the years, then dive into YOLO theory and a programmatic implementation using Tensorflow! Code for this video: https://github.com/llSourcell/YOLO_Object_Detection Please Subscribe! And like. And comment. That's what keeps me going. Want more inspiration & education? Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology More learning resources: https://pjreddie.com/darknet/yolo/ https://timebutt.github.io/static/how-to-train-yolov2-to-detect-custom-objects/ http://machinethink.net/blog/object-detection-with-yolo/ https://github.com/pjreddie/darknet/wiki/YOLO:-Real-Time-Object-Detection https://github.com/KleinYuan/easy-yolo https://medium.com/@xslittlegrass/almost-real-time-vehicle-detection-using-yolo-da0f016b43de https://medium.com/diaryofawannapreneur/yolo-you-only-look-once-for-object-detection-explained-6f80ea7aaa1e Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Instagram: https://www.instagram.com/sirajraval/
https://wn.com/Yolo_Object_Detection
How computers learn to recognize objects instantly | Joseph Redmon
7:38

How computers learn to recognize objects instantly | Joseph Redmon

  • Order:
  • Duration: 7:38
  • Updated: 18 Aug 2017
  • views: 246678
videos
Ten years ago, researchers thought that getting a computer to tell the difference between a cat and a dog would be almost impossible. Today, computer vision systems do it with greater than 99 percent accuracy. How? Joseph Redmon works on the YOLO (You Only Look Once) system, an open-source method of object detection that can identify objects in images and video -- from zebras to stop signs -- with lightning-quick speed. In a remarkable live demo, Redmon shows off this important step forward for applications like self-driving cars, robotics and even cancer detection. Check out more TED talks: http://www.ted.com The TED Talks channel features the best talks and performances from the TED Conference, where the world's leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design -- plus science, business, global issues, the arts and more. Follow TED on Twitter: http://www.twitter.com/TEDTalks Like TED on Facebook: https://www.facebook.com/TED Subscribe to our channel: https://www.youtube.com/TED
https://wn.com/How_Computers_Learn_To_Recognize_Objects_Instantly_|_Joseph_Redmon
Computer Vision with MATLAB for Object Detection and Tracking
46:57

Computer Vision with MATLAB for Object Detection and Tracking

  • Order:
  • Duration: 46:57
  • Updated: 28 Apr 2017
  • views: 37339
videos
Download a trial: https://goo.gl/PSa78r See what's new in the latest release of MATLAB and Simulink: https://goo.gl/3MdQK1 Computer vision uses images and video to detect, classify, and track objects or events in order to understand a real-world scene. In this webinar, we dive deeper into the topic of object detection and tracking. Through product demonstrations, you will see how to: Recognize objects using SURF features Detect faces and upright people with algorithms such as Viola-Jones Track single objects with the Kanade-Lucas-Tomasi (KLT) point tracking algorithm Perform Kalman Filtering to predict the location of a moving object Implement a motion-based multiple object tracking system This webinar assumes some experience with MATLAB and Image Processing Toolbox. We will focus on the Computer Vision System Toolbox. About the Presenter: Bruce Tannenbaum works on image processing and computer vision applications in technical marketing at MathWorks. Earlier in his career, he developed computer vision and wavelet-based image compression algorithms at Sarnoff Corporation (SRI). He holds an MSEE degree from University of Michigan and a BSEE degree from Penn State. View example code from this webinar here: http://www.mathworks.com/matlabcentral/fileexchange/40079
https://wn.com/Computer_Vision_With_Matlab_For_Object_Detection_And_Tracking
How To Detect Objects with a CLICK PLC
4:10

How To Detect Objects with a CLICK PLC

  • Order:
  • Duration: 4:10
  • Updated: 04 May 2015
  • views: 3914
videos
http://www.AutomationDirect.com/click-plc (VID-CL-0022) - Learn how to connect any PNP or NPN proximity, photo electric or ultrasonic sensor and mechanical switches to a CLICK PLC for object sensing and detection. To learn more visit http://www.automationdirect.com/click-plc To SUBSCRIBE: http://www.youtube.com/subscription_center?add_user=automationdirect Facebook: http://www.AutomationDirect.com/Facebook Twitter: http://www.AutomationDirect.com/Twitter Google: http://www.AutomationDirect.com/google-plus Related AutomationDirect.com part numbers: C0-00DD1-D, C0-00DD2-D, C0-00DR-D, C0-00AR-D, C0-01DD1-D, C0-01DD2-D, C0-01DR-D, C0-01AR-D, C0-02DD1-D, C0-02DD2-D, C0-02DR-D, C0-10DD1E-D, C0-10DD2E-D, C0-10DRE-D, C0-10DRE-D, C0-11DD1E-D, C0-11DD2E-D, C0-11DRE-D, C0-11ARE-D, C0-12DD1E-D, C0-12DD2E-D, C0-12DRE-D, C0-12ARE-D, C0-12DD1E-1-D, C0-12DD2E-1-D, C0-12DRE-1-D, C0-12ARE-1-D, C0-12DD1E-2-D, C0-12DD2E-2-D, C0-12DRE-2-D, C0-12ARE-2-D, C0-08ND3, C0-08ND3-1, C0-16ND3, C0-08TD1, C0-08TD2, C0-08NE3, C0-16TD1, C0-16TD2, C0-16NE3, C0-08CDR, C0-16CDD1, C0-16CDD2, C0-08NA, C0-08TA, C0-08TR, C0-04AD-1, C0-04AD-2, C0-04DA-1, C0-04DA-2, C0-4AD2DA-1, C0-4AD2DA-2, C0-04RTD, C0-04THM, C0-PGMSW
https://wn.com/How_To_Detect_Objects_With_A_Click_Plc
Object Detection and Recogition
1:30

Object Detection and Recogition

  • Order:
  • Duration: 1:30
  • Updated: 31 Aug 2010
  • views: 197432
videos
http://www.willowgarage.com/blog/2010/09/20/scalable-object-recognition
https://wn.com/Object_Detection_And_Recogition
Matlab object tracking using webcam tutorial Matlab ( detect red )
8:26

Matlab object tracking using webcam tutorial Matlab ( detect red )

  • Order:
  • Duration: 8:26
  • Updated: 07 Mar 2015
  • views: 82977
videos
A complete tutorial with source code explained using live video feed from webcam and track red colored objects. We use image acquisition tool box. For more tutorials and matlabcode Visit: http://www.solved4u.weebly.com
https://wn.com/Matlab_Object_Tracking_Using_Webcam_Tutorial_Matlab_(_Detect_Red_)
How To Detect Objects with a Productivity Series Controller
4:30

How To Detect Objects with a Productivity Series Controller

  • Order:
  • Duration: 4:30
  • Updated: 04 May 2015
  • views: 2781
videos
http://www.AutomationDirect.com//p2000 (VID-P2-0003) - Learn how to connect any PNP or NPN proximity, photo electric or ultrasonic sensor and mechanical switches to a Productivity Series controller for object sensing and detection. A Productivity 2000 controller is used in this video, but is also applicable to the Productivity 3000. To learn more visit http://www.automationdirect.com//p2000 To SUBSCRIBE: http://www.youtube.com/subscription_center?add_user=automationdirect Facebook: http://www.AutomationDirect.com/Facebook Twitter: http://www.AutomationDirect.com/Twitter Google: http://www.AutomationDirect.com/google-plus Related AutomationDirect.com part numbers: P1-540, P1-START, MICSD-16G, P1-01AC, P1-08ND3, P1-08TD1, P1-08TD2, P1-15CDD1, P1-15CDD2, P1-16CDR, P1-08TRS, P1-16TR, P1-04ADL-1, P1-04ADL-2, P1-04DAL-1, P1-04DAL-2, P1-04THM, P1-04NTC, P1-08SIM, PS-PGMSW, P2-550, P2-RS, P2-START, P2-04B, P2-07B, P2-11B, P2-15B, P2-01AC, P2-01DCAC, P2-08ND3-1, P2-08NE3, P2-16ND3-1, P2-16NE3, P2-16NE3, P2-32ND3-1, P2-32NE3, P2-08TD1S, P2-08TD2S, P2-08TD1P, P2-08TD2P, P2-15TD1, P2-15TD2, P2-16TD1P, P2-16TD2P, P2-32TD1P, P2-32TD2P, P2-08NAS, P2-16NA, P2-08TAS, P2-16TA, P2-08TRS, P2-16TR, P2-04AD, P2-08AD-1, P2-08AD-2, P2-08ADL-1, P2-08ADL-2, P2-16AD-1, P2-16AD-2, P2-16ADL-1, P2-16ADL-2, P2-04DA, P2-04DAL-1, P2-04DAL-2, P2-08DA-1, P2-08DA-2, P2-16DA-1, P2-16DA-2, P2-08DAL-1, P2-08DAL-2, P2-16DAL-1, P2-16DAL-2, P2-8AD4DA-1, P2-8AD4DA-2, P2-08THM, P2-06RTD, P2-08NTC, P2-SCM, P2-HSI, P2-HSO, P2-08SIM, P3-550E, P3-550, P3-530, P3-RS, P3-RX, P3-EX, P3-03B, P3-05B, P3-08B, P3-11B, P3-01AC, P3-01DC, P3-08ND3S, P3-16ND3, P3-32ND3, P3-64ND3, P3-08TD1S, P3-08TD2S, P3-16TD1, P3-16TD2, P3-16TD3P, P3-32TD1, P3-32TD2, P3-64TD1, P3-64TD2, P3-08NAS, P3-16NA, P3-08TAS, P3-16TA, P3-08TRS, P3-08TRS-1, P3-16TR, P3-04ADS, P3-08AD, P3-16AD-1, P3-16AD-2, P3-08RTD, P3-08THM, P3-04DA, P3-08DA-1, P3-08DA-2, P3-06DAS-1, P3-06DAS-2, P3-16DA-1, P3-16DA-2, P3-8AD4DA-1, P3-8AD4DA-2, P3-SCM, P3-HSI, P3-HSO, P3-16SIM, PS-PGMSW Software Version used in this video: Productivity Suite Programming Software Version 2.0.0 (44)
https://wn.com/How_To_Detect_Objects_With_A_Productivity_Series_Controller
Object detection with Tensorflow - Self Driving Cars p.17
12:37

Object detection with Tensorflow - Self Driving Cars p.17

  • Order:
  • Duration: 12:37
  • Updated: 04 Sep 2017
  • views: 48042
videos
Hello and welcome to another Python and self-driving cars tutorial. In this tutorial, we're going to cover the implementation of the TensorFlow Object Detection API into the realistic simulation environment that is GTAV. Due to the realistic representations that occur inside of GTAV, we can use object detectors that were made for the real-world, and still see success. For example, we can detect cars, people, stop signs, trucks, and stop lights. Text tutorials and sample code: https://pythonprogramming.net/tensorflow-object-detection-api-self-driving-car/ https://twitter.com/sentdex https://www.facebook.com/pythonprogramming.net/ https://plus.google.com/+sentdex
https://wn.com/Object_Detection_With_Tensorflow_Self_Driving_Cars_P.17
How to Detect Color Objects with OpenCV C++
1:51

How to Detect Color Objects with OpenCV C++

  • Order:
  • Duration: 1:51
  • Updated: 19 Apr 2014
  • views: 92673
videos
Please visit us at http://opencv-srf.blogspot.com/2010/09/object-detection-using-color-seperation.html for more information on how to detect color objects with OpenCV/C++
https://wn.com/How_To_Detect_Color_Objects_With_Opencv_C
Basic EV3 program to Detect and Push objects
0:23

Basic EV3 program to Detect and Push objects

  • Order:
  • Duration: 0:23
  • Updated: 21 Apr 2016
  • views: 1259
videos
Basic EV3 program to Detect and Push objects
https://wn.com/Basic_Ev3_Program_To_Detect_And_Push_Objects
Bosch Universal Detector D-Tect 120 [Detect Live Cables, Metal, Wooden Object, Water Pipes]
1:17

Bosch Universal Detector D-Tect 120 [Detect Live Cables, Metal, Wooden Object, Water Pipes]

  • Order:
  • Duration: 1:17
  • Updated: 25 Jan 2017
  • views: 825
videos
The most convenient universal detector for reliable detection of all materials including plastic Product Features - Innovative center finder technology gives direction indication for precise location of object center - Spot measurement enables you to perform measurement with great ease - Reliable detection of all objects with an easy user interface featuring 3 mode buttons Purchase Link : http://hardwarespecialist.com.sg/product/bosch-professional-d-tect-120/ Retail Address: 10 Kaki Bukit Road 2 #01-02 First East Centre Singapore 417868
https://wn.com/Bosch_Universal_Detector_D_Tect_120_Detect_Live_Cables,_Metal,_Wooden_Object,_Water_Pipes
How to Detect an Object with Robotiq Grippers
1:33

How to Detect an Object with Robotiq Grippers

  • Order:
  • Duration: 1:33
  • Updated: 16 May 2016
  • views: 1025
videos
http://robotiq.com/products/ This video will explain you how to detect an object with Robotiq Grippers. If you want to know more about object detection with the Robotiq Grippers, look at the online instruction manual available at http://support.roboptiq.com.
https://wn.com/How_To_Detect_An_Object_With_Robotiq_Grippers
Chinese Street surveillance.  Object / Face Recognition.
11:20

Chinese Street surveillance. Object / Face Recognition.

  • Order:
  • Duration: 11:20
  • Updated: 23 Sep 2017
  • views: 161852
videos
Part of the "sense" line of real time video analysis. Click Here To Subscribe! ►https://www.youtube.com/channel/UCseFtoNUVuegUgM3s60sE4A?sub_confirmation=1 Twitter ► https://twitter.com/ID_R_McGregor
https://wn.com/Chinese_Street_Surveillance._Object_Face_Recognition.
How To Detect Objects with a Do-more PLC
3:49

How To Detect Objects with a Do-more PLC

  • Order:
  • Duration: 3:49
  • Updated: 04 May 2015
  • views: 1020
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http://www.AutomationDirect.com/Do-more-PLCs (VID-DM-0023) - Learn how to connect any PNP or NPN proximity, photo electric or ultrasonic sensor and mechanical switches to a Do-more PLC for object sensing and detection. A Do-more H2-DM1E is used in this video, but is also applicable to the T1H-DM1x Terminator PLCs. To learn more visit http://www.automationdirect.com/Do-more-PLCs To SUBSCRIBE: http://www.youtube.com/subscription_center?add_user=automationdirect Facebook: http://www.AutomationDirect.com/Facebook Twitter: http://www.AutomationDirect.com/Twitter Google: http://www.AutomationDirect.com/google-plus Related AutomationDirect.com part numbers: BX-DM1E-M-D, BX-DM1E-M, BX-DM1-10AR-D, BX-DM1-10ER-D, BX-DM1-10ED1-D, BX-DM1-10ED2-D, BX-DM1E-10AR3-D, BX-DM1E-10ER3-D, BX-DM1E-10ED13-D, BX-DM1E-10ED23-D, BX-RTB10, BX-RTB10-1, BX-RTB10-2, BX-DM1-18ER-D, BX-DM1-18ED2-D, BX-DM1-18ED1-D, BX-DM1E-18ER3-D, BX-DM1E-18ED23-D, BX-DM1E-18ED13-D, BX-DM1-18AR, BX-DM1-18ER, BX-DM1-18ED2, BX-DM1-18ED1, BX-DM1E-18AR3, BX-DM1E-18ER3, BX-DM1E-18ED23, BX-DM1E-18ED13, BX-RTB18, BX-RTB18-1, BX-RTB03, BX-RTB03-1, BX-RTB05, BX-RTB05-1, BX-RTB05-2, BX-RTB06, BX-RTB06-1, BX-DM1-36ER-D, BX-DM1-36ED2-D, BX-DM1-36ED1-D, BX-DM1E-36ER3-D, BX-DM1E-36ED23-D, BX-DM1E-36ED13-D, BX-DM1-36ER, BX-DM1-36AR, BX-DM1-36ED2, BX-DM1-36ED1, BX-DM1E-36ER3, BX-DM1E-36AR3, BX-DM1E-36ED23, BX-DM1E-36ED13, BX-RTB36, BX-RTB36-1, BX-P-SER2-RJ12, BX-P-SER2-TERM, BX-P-SER4-TERM, BX-P-USB-B, BX-P-ECOMLT, BX-RTB03S, BX-08ND3, BX-12ND3, BX-16ND3, BX-08NF3, BX-08TD1, BX-08TD2, BX-12TD1, BX-12TD2, BX-16TD1, BX-16TD2, BX-08CD3R, BX-12CD3D1, BX-12CD3D2, BX-16CD3D1, BX-16CD3D2, BX-RTB08, BX-RTB08-1, BX-RTB08-2, BX-08NB, BX-12NB, BX-16NB, BX-08NA, BX-12NA, BX-16NA, BX-08TA, BX-12TA, BX-08TR, BX-12TR, BX-16TR, BX-05TRS, BX-08AD-1, BX-08AD-2B, BX-08DA-1, BX-08DA-2B, BX-04THM, BX-PGM-CBL, BX-DM1-START, BX-DM1E-START, H2-DM1, H2-DM1E, H2-DM1-START, H2-DM1E-START, T1H-DM1E, T1H-DM1, T1H-CTRIO, T1H-08TDS, DM-PGMSW Software Version used in this video: Do-more Designer 1.3.1
https://wn.com/How_To_Detect_Objects_With_A_Do_More_Plc
MIT’s “CornerCameras” system can detect objects or people in a Hidden Scene
2:03

MIT’s “CornerCameras” system can detect objects or people in a Hidden Scene

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  • Duration: 2:03
  • Updated: 10 Oct 2017
  • views: 377
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MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers have developed a new system named as “CornerCameras”, to detect objects or people in a hidden scene and measure their speed and trajectory — all in real-time. This “CornerCameras” system can work with smartphone cameras to see things hidden around corners. To explain, imagine that you’re walking down an L-shaped hallway and have a wall between you and some objects around the corner. Those objects reflect a small amount of light on the ground in your line of sight, creating a fuzzy shadow that is referred to as the “penumbra.” Using video of the penumbra, the system can stitch together a series of one-dimensional images that reveal information about the objects around the corner. The team was surprised to find that CornerCameras worked in a range of challenging situations, including weather conditions like rain. The ability to see around obstructions would be useful for many tasks, from firefighters finding people in burning buildings to drivers detecting pedestrians in their blind spots. Most approaches for seeing around obstacles involve special lasers. Specifically, researchers shine cameras on specific points that are visible to both the observable and hidden scene, and then measure how long it takes for the light to return. However, these so-called “time-of-flight cameras” are expensive and can easily get thrown off by ambient light, especially outdoors. In contrast, the CSAIL team’s technique doesn’t require actively projecting light into the space, and works in a wider range of indoor and outdoor environments and with off-the-shelf consumer cameras. News Source: http://news.mit.edu/2017/artificial-intelligence-for-your-blind-spot-mit-csail-cornercameras-1009 Video Source/Credit: MITCSAIL
https://wn.com/Mit’S_“Cornercameras”_System_Can_Detect_Objects_Or_People_In_A_Hidden_Scene
detect objects
0:18

detect objects

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  • Duration: 0:18
  • Updated: 14 Feb 2017
  • views: 2
videos
https://wn.com/Detect_Objects
26 - How to Detect Mouse Click or Touch on a GameObject
6:48

26 - How to Detect Mouse Click or Touch on a GameObject

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  • Duration: 6:48
  • Updated: 05 Feb 2017
  • views: 6241
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In this video you will learn how to detect a mouse click or tap on a gameobject with the help of ray and raycast. Download Code : https://drive.google.com/open?id=0B__1zp7jwQOKT1NiamoyMFlDaVE
https://wn.com/26_How_To_Detect_Mouse_Click_Or_Touch_On_A_Gameobject
Introduction to CoreML: Detect Dominant Object on an Image (Swift 4 & XCode 9)
17:07

Introduction to CoreML: Detect Dominant Object on an Image (Swift 4 & XCode 9)

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  • Duration: 17:07
  • Updated: 19 Sep 2017
  • views: 509
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In this video, we will go through an introduction on CoreML detecting the dominant object in an image. Project: http://bit.ly/2xOgswO Follow Me: Twitter: https://twitter.com/VasilNunev Instagram: https://instagram.com/v.nunev iTunes: https://itunes.apple.com/us/developer/vasil-nunev/id1263932026
https://wn.com/Introduction_To_Coreml_Detect_Dominant_Object_On_An_Image_(Swift_4_Xcode_9)
Detect object name and meaning
1:09

Detect object name and meaning

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  • Duration: 1:09
  • Updated: 08 Feb 2018
  • views: 25
videos
Find out the name and meaning of objects by taking a photo of them. Ability to take a photo of one specific object which user does not the meaning of that. The camera would detect the object name by the power of machine learning and then the definition and meaning and example for this object would be shown to the user automatically and then save them on the device. App in iTunes: https://itunes.apple.com/us/app/ielts-speaking-master/id1329270990?mt=8
https://wn.com/Detect_Object_Name_And_Meaning
River Treasure! - Iphone 6, Camera, Rings, Knives and More!
16:55

River Treasure! - Iphone 6, Camera, Rings, Knives and More!

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  • Duration: 16:55
  • Updated: 27 Jul 2016
  • views: 6654041
videos
What an Amazing Adventure out on the river! I found lots of awesome things with my AT Pro, while searching for my friend's lost wedding ring. After 10 hours of Metal Detecting I recovered many rings, one is a 14K Gold wedding band, but it is not the one I was looking for. Joe's ring is still somewhere in the river, next time we may find it. My best finds from this trip are the Iphone 6 (Which I had returned to the owner), The Rings, Waterproof Lumix Camera and the nice shades. Link to the metal detector I use: https://www.battleground-detectors.com/shop/garrett-metal-detectors/94-garrett-at-pro-pro-pointer-at.html This video was filmed with my Olympus camera. Here's the link http://amzn.to/2ki8HIG , these camera are rugged! I will have more videos of detecting in the river coming soon! Thank you for watching and God Bless! "On the last day of the feast, the great day, Jesus stood up and cried out, " If anyone thrists, let him come to me and drink. Whoever believes in me, as the Scripture has said, 'Out of his heart will flow rivers of living water.' " - John 7:37-38 "Take my instruction instead of silver, and knowledge rather than choice gold, for wisdom is better than jewels, and all that you may desire cannot compare with her." - Proverbs 8:10-11 Isaiah 40:8
https://wn.com/River_Treasure_Iphone_6,_Camera,_Rings,_Knives_And_More
Unity3D How to : Detect Mouse Click on an Object
1:34

Unity3D How to : Detect Mouse Click on an Object

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  • Duration: 1:34
  • Updated: 21 Oct 2014
  • views: 48889
videos
This is how to check if there's a mouse click on n object attached with collider(or collider2D) and then do anything you want :) If you think this tutorial is useful, don't forget to like - share - subscribe. And here is my game for Android https://play.google.com/store/apps/details?id=com.tawan.kiu
https://wn.com/Unity3D_How_To_Detect_Mouse_Click_On_An_Object
Lecture 11 | Detection and Segmentation
1:14:26

Lecture 11 | Detection and Segmentation

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  • Duration: 1:14:26
  • Updated: 11 Aug 2017
  • views: 64783
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In Lecture 11 we move beyond image classification, and show how convolutional networks can be applied to other core computer vision tasks. We show how fully convolutional networks equipped with downsampling and upsampling layers can be used for semantic segmentation, and how multitask losses can be used for localization and pose estimation. We discuss a number of methods for object detection, including the region-based R-CNN family of methods and single-shot methods like SSD and YOLO. Finally we show how ideas from semantic segmentation and object detection can be combined to perform instance segmentation. Keywords: Semantic segmentation, fully convolutional networks, unpooling, transpose convolution, localization, multitask losses, pose estimation, object detection, sliding window, region proposals, R-CNN, Fast R-CNN, Faster R-CNN, YOLO, SSD, DenseCap, instance segmentation, Mask R-CNN Slides: http://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture11.pdf -------------------------------------------------------------------------------------- Convolutional Neural Networks for Visual Recognition Instructors: Fei-Fei Li: http://vision.stanford.edu/feifeili/ Justin Johnson: http://cs.stanford.edu/people/jcjohns/ Serena Yeung: http://ai.stanford.edu/~syyeung/ Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. Core to many of these applications are visual recognition tasks such as image classification, localization and detection. Recent developments in neural network (aka “deep learning”) approaches have greatly advanced the performance of these state-of-the-art visual recognition systems. This lecture collection is a deep dive into details of the deep learning architectures with a focus on learning end-to-end models for these tasks, particularly image classification. From this lecture collection, students will learn to implement, train and debug their own neural networks and gain a detailed understanding of cutting-edge research in computer vision. Website: http://cs231n.stanford.edu/ For additional learning opportunities please visit: http://online.stanford.edu/
https://wn.com/Lecture_11_|_Detection_And_Segmentation
Russia: These devices could help special forces detect enemies through walls
2:43

Russia: These devices could help special forces detect enemies through walls

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  • Duration: 2:43
  • Updated: 18 Nov 2016
  • views: 2548
videos
Russia's Logis-Geotech demonstrated two detection devices which the company says are capable of detecting objects and people through thick concrete walls, in Moscow on Friday. The firm says the detectors could be critical in combat operations. The radars are said to be extremely sensitive and can detect a person breathing even if he remains still and does not move at all. Andrei Padenko, Representative of Logis-Geotech Group (Russian): "[We are presenting] two devices. RO-400 is a stationary device that is mounted against a wall and has the maximum range of detection. It can detect [signals] through 60 centimetre (23 inch)-thick concrete walls and even through two walls. The RO-900 is a portable device. Its [total] range of detection is a bit lower, up to 11 meters (36 feet), and it can be carried around by a soldier." Andrei Padenko, Representative of Logis-Geotech Group (Russian): "The main users are the Special Services units to whom this kind of information is critical. This kind of information may cost the lives of many servicemen because they [generally] do not know who is inside a closed room, how many people are there and what they are doing [there]. The devices are built for these purposes." Igor Vedeneyev, Head Engineer of Reconnaissance Department at Logis-Geotech (Russian): "Our device differs [from others] in its ability to detect objects behind two or three obstacles depending on the thickness of these obstacles. Besides, it has a wider view of some 180 degrees. Hence, a person who is standing at the other side of the wall will be detected from 1.5 metres (4.9 feet) to three metres (9.8 feet) away." Video ID: 20161118- 020 Video on Demand: http://www.ruptly.tv Contact: cd@ruptly.tv Twitter: http://twitter.com/Ruptly Facebook: http://www.facebook.com/Ruptly
https://wn.com/Russia_These_Devices_Could_Help_Special_Forces_Detect_Enemies_Through_Walls
Schauenburg : dotNetix - Using Deep Neural Networks to detect objects in a road scene.
6:22

Schauenburg : dotNetix - Using Deep Neural Networks to detect objects in a road scene.

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  • Duration: 6:22
  • Updated: 23 Jan 2018
  • views: 99
videos
Schauenburg/dotNetix develops collision avoidance systems. This is a demonstrator of how our Deep Neural Network implimentation to detect vehicles and people. The driver of the vehicle is warned of a potential collision with the object.
https://wn.com/Schauenburg_Dotnetix_Using_Deep_Neural_Networks_To_Detect_Objects_In_A_Road_Scene.
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