Research-Papers

List of all research papers I have read. This place is to remind me of my progress in the DL realm.

Keep asking yourself:

1. What author is trying to accomplish?
2. What you can use of it?
3. What are key elements?
4. What other references you want to follow?

Depending on importance go to higher level:
Level 1: Read title, abstract and figures
Level 2: Read intro, Conclusion and skip related work section
Level 3: Read Medium or other articles or blogs
Level 4: Read some sections of it
Level 5: Read some more sections of it
Level 6: Implement completely or partially in a project
Level 7: Read through and between every line.

Research Paper	Note	Progress (%)
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks	Wiki	80%
Very Deep convolutional Networks for Large Scale Image Recognition	Wiki	75%
Deep Residual Learning for Image Recognition	Wiki	80%
Convolutional Sequence to Sequence Learning	Wiki	45%
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift	Wiki	75%
Densely Connected Convolutional Networks	Wiki	75%
Libra R-CNN: Towards Balanced Learning for Object Detection	Wiki	10%
Bridging the Gaps Between Residual Learning,Recurrent Neural Networks and Visual Cortex	here	0%

Acknowledgements

1. Prof. Surekha Bhanot for making me realise the importance of reading.
2. Prof. Andrew Ng for teaching me how to learn, research and stay updated.
3. Prof. Jeremy Howard for being guiding star for how to implement ideas in codes.