Solved – Are there networks specialised on object detection for a single class of object

image processingneural networksobject detection

I want to detect the location of a single class of object, which might occur multiple times in an image. Specifically, this relates to research on detecting brake lights for autonomous vehicles. I imagine similar techniques could be used to detect all faces for security applications, or balls for robot soccer, or a specific type of cancer or…

At the moment I am considering retraining a YOLO9000 or SSD network, as both have the necessary real-time performance to run 30fps. However, I'm assuming that at least some of their capacity is dedicated to features I don't need

  • classification across a wide range of classes
  • detecting whether something is an object or not for any of these classes

Since my problem is much simpler, I wondered whether there are any network architectures which have specialised on the localisation task?

I have found similar questions, but in both cases the question I want an answer to was mixed up with a secondary question and didn't give the answer I was looking for. I'd be happy to close as a dupe if one of these gets a better answer:

https://stackoverflow.com/questions/45891271/neural-network-to-detect-one-class-of-object-only
https://ai.stackexchange.com/questions/2279/cnn-for-detecting-not-just-the-nature-of-the-object-but-position-within-image-a

I did learn one helpful thing from those questions: trying to detect a single class is actually differentiating between 2 classes – objects I want to detect and background/everything else.

Best Answer

I am currently doing a single class segmentation network to detect pixels in microscopy images. What I am doing is like one step more than what you need to do.

Basically I am using FCN-8 to do pixel classification, but the first part of the model is a VGG16.

I would look online for a generic Keras or other library VGG16 model, and retrain it on your dataset.

This implies that you have a large enough dataset to train the model with and some time in front of you as they require a long training to be really accurate.

One article that might be of help: https://alexisbcook.github.io/2017/global-average-pooling-layers-for-object-localization/

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