Answers.Body: <p>We are getting there, with as usual some trade-off between quality and speed.</p>
  <p>For example <a href="http://cs231n.stanford.edu/slides/2016/winter1516_lecture8.pdf" rel="nofollow noreferrer">Lecture 8: Spatial Localization and Detection lecture</a> shows some benchmarks (mAP = Mean Average Precision, higher is better; FPS = frame per second):</p>
  <p><a href="https://i.sstatic.net/AfHt2m.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/AfHt2m.png" alt="Table/Performance: Real-Time Detectors" /></a></p>
  <p><a href="https://i.sstatic.net/B5Qb9m.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/B5Qb9m.png" alt="Table/Performance: R-CNN, Fast R-CNN, Faster R-CNN" /></a></p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2016-08-08T04:14:49.693Z
Answers.LastActivityDate: 2020-11-12T21:30:17.417Z
Answers.LastEditDate: 2020-11-12T21:30:17.417Z
Answers.UserDisplayName: Franck Dernoncourt
Body: <p>Convolutional neural network are leading type of feed-forward artificial neural network for image recognition. Can they be used for real-time image recognition for videos (frame by frame), or it takes too much processing (assuming they're written in C-like language)?</p>
  
  <p>For example for classification of type of animals based on the training from huge dataset.</p>
  
Tags: <convolutional-neural-networks><classification><performance><real-time>
Title: Can ConvNets be used for real-time object recognition from video feed?
UserDisplayName: kenorb
ThreadText: # Can ConvNets be used for real-time object recognition from video feed?
  
  (Asked by: username_0 on 2016-08-07)
  
  Convolutional neural network are leading type of feed-forward artificial neural network for image recognition. Can they be used for real-time image recognition for videos (frame by frame), or it takes too much processing (assuming they're written in C-like language)?
  
  For example for classification of type of animals based on the training from huge dataset.
  
  **Tags:** convolutional-neural-networks, classification, performance, real-time
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2016-08-08. Score: 2 | Accepted answer
  
  We are getting there, with as usual some trade-off between quality and speed.
  
  For example [Lecture 8: Spatial Localization and Detection lecture](http://cs231n.stanford.edu/slides/2016/winter1516_lecture8.pdf) shows some benchmarks (mAP = Mean Average Precision, higher is better; FPS = frame per second):
  
  [![Table/Performance: Real-Time Detectors](https://i.sstatic.net/AfHt2m.png)](https://i.sstatic.net/AfHt2m.png)
  
  [![Table/Performance: R-CNN, Fast R-CNN, Faster R-CNN](https://i.sstatic.net/B5Qb9m.png)](https://i.sstatic.net/B5Qb9m.png)
  
  
  ---
  
  