Summary

In this chapter, we went through different state of the art approaches in object detection such as R-CNN, Fast R-CNN, Faster R-CNN, YOLO, SSD, and others. Furthermore, we explored an approach given by Hierarchical Object Detection with Deep Reinforcement Learning by Bellver et. al. (2016). As per this approach we learnt how to create an MDP framework for object detection and hierarchically detect objects in a top-bottom exploration approach in minimal time steps. Object detection in an image is one application in computer vision. There are other domains such as object detection in videos, video tagging, and many more where reinforcement learning can create state of the art learning agents.

In the next chapter, we will learn how reinforcement learning can be applied in the domain of NLP (natural language processing).

 

 

 

 

 

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