Object Detection: An End to End Theoretical Perspective

I will be sure to correct myself and post.References:http://cs231n.github.io/transfer-learning/#tfhttp://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture11.pdfEfficient Graph-Based Image Segmentation -http://people.cs.uchicago.edu/~pff/papers/seg-ijcv.pdfRich feature hierarchies for accurate object detection and semantic segmentation(RCNN Paper)- https://arxiv.org/pdf/1311.2524.pdfSelective Search for Object Recognitionhttps://deepsense.ai/region-of-interest-pooling-explained/https://towardsdatascience.com/fasterrcnn-explained-part-1-with-code-599c16568cffhttps://stackoverflow.com/questions/48163961/how-do-you-do-roi-pooling-on-areas-smaller-than-the-target-sizehttps://medium.com/@smallfishbigsea/faster-r-cnn-explained-864d4fb7e3f8https://tryolabs.com/blog/2018/01/18/faster-r-cnn-down-the-rabbit-hole-of-modern-object-detection/Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkshttps://www.slideshare.net/WenjingChen7/deep-learning-for-object-detection. More details

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