All the useful materials related to Deep Learning and Computer Vision
Keras Functional Model | How to build non-linear Neural Networks? https://www.youtube.com/watch?v=OvQQP1QVru8&t=1143s
What is Transfer Learning? Transfer Learning in Keras | Fine Tuning Vs Feature Extraction:
https://www.youtube.com/watch?v=WWcgHjuKVqA&list=PLKnIA16_RmvYuZauWaPlRTC54KxSNLtNn&index=53
UCF CRCV : https://www.youtube.com/@UCFCRCV/playlists
Daniel Bourke: https://www.youtube.com/@mrdbourke/videos
Daniel Bourke ArXiV: https://www.youtube.com/@danielbourkearxiv2821/playlists
https://www.youtube.com/@ComputerVisionFoundation/videos
Research Paper YT: https://www.youtube.com/@OpenlifesciAI/videos
Learning Pytorch
https://www.youtube.com/watch?v=Z_ikDlimN6A&t=89037s
COCO dataset: https://cocodataset.org/#explore
Documentation: https://docs.ultralytics.com/datasets/detect/coco/
Research papers (for learning/ basics)
Dropout: A Simple Way to Prevent Neural Networks from Overfitting - > https://www.jmlr.org/papers/volume15/srivastava14a/srivastava14a.pdf
Convo Demo : https://deeplizard.com/resource/pavq7noze2
LeNet Paper: https://axon.cs.byu.edu/~martinez/classes/678/Papers/Convolution_nets.pdf
ImageNet Paper: https://proceedings.neurips.cc/paper/2012/hash/c399862d3b9d6b76c8436e924a68c45b-Abstract.html
AlexNet: https://www.youtube.com/watch?v=UZDiGooFs54
LSTM: https://www.youtube.com/watch?v=1yvBqasHLZs
VGG16 Neural Network Visualization: https://www.youtube.com/watch?v=RNnKtNrsrmg
ResNet: https://arxiv.org/abs/1512.03385
Inception : https://arxiv.org/pdf/1409.4842
https://proceedings.neurips.cc/paper/2013/file/71f6278d140af599e06ad9bf1ba03cb0-Paper.pdf
https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=772891a6a2955f4927d16c9e8690419e75d54310
https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=04d0b6952a4f0c7203577afc9476c2fcab2cba06
https://www.cell.com/heliyon/pdf/S2405-8440(18)33206-7.pdf
https://books.google.com.bd/books?hl=en&lr=&id=ZEID3w9STOUC&oi=fnd&pg=PP7&dq=neural+network&ots=sALxx0XH2L&sig=Z4gHtsa4zcKeDMCyqgK1hAGawuA&redir_esc=y#v=onepage&q=neural%20network&f=false
https://repositories.nust.edu.pk/xmlui/bitstream/handle/123456789/41863/Artificial%20Neural%20Networks%20Methods%20and%20Applications%20by%20David%20J.%20Livingstone.pdf?sequence=1&isAllowed=y#page=24
https://d1wqtxts1xzle7.cloudfront.net/102219543/j.1551-8833.2007.tb07961.x20230514-1-w63ifm-libre.pdf?1684103424=&response-content-disposition=inline%3B+filename%3DArtificial_neural_network_real_time_proc.pdf&Expires=1744197226&Signature=B2yTJNBAnzfAAaPrTMNJiO4c0KvGQMlxgHsVWKd78ZRjtTbTSQYVdxQQ6j94c89Z-jTKyJuAVp4XYok9zHnlylxVlk~A1ZZwD-4MUjkazmewK9GsdqwaWi9e8ty7ocLEca0qNINFoeirkrpMW~eCI~sVDqHn8htSfbdWijU-rOjI0ZAzKXwbSQ4TggJqQZx3XOz2oLZ1K~txHIUG6H9MvNL9oB2IP9XNGlwz1-dEDW7b3HMHMIqcpP1kkZRCoCnUesB83q5vcYpfy7J4L0mNE411FYkq7y3XJcaiLT3fg7qUrPLHpBjdgg~ZqyvXH5UEFzVfX6EIITShOdz2E-prLA__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA
https://link.springer.com/article/10.1007/s11277-017-5224-x
https://link.springer.com/chapter/10.1007/978-1-4615-0377-4_5
https://www.nature.com/articles/s41583-020-0277-3
https://link.springer.com/chapter/10.1007/978-3-642-61068-4_7