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README.md		README.md
mixed_input_dl.py		mixed_input_dl.py
nlp_experiments.ipynb		nlp_experiments.ipynb
nn_tutorial_pytorch.ipynb		nn_tutorial_pytorch.ipynb
parallel_tf.PNG		parallel_tf.PNG
patchify.py		patchify.py
srcnn_keras_austin_evaluation_playground.py		srcnn_keras_austin_evaluation_playground.py
stratifiedkfold.ipynb		stratifiedkfold.ipynb
wrf_python.ipynb		wrf_python.ipynb

README.md

Important resources

Microsoft COCO paper: https://arxiv.org/pdf/1405.0312.pdf
Color models: https://www.wigglepixel.nl/en/blog/what-are-color-models/
Scale invariant feature transform (SIFT): https://www.analyticsvidhya.com/blog/2019/10/detailed-guide-powerful-sift-technique-image-matching-python/
Selective search for object detection: https://sahiltinky94.medium.com/selective-search-for-object-recognitions-eca15dc9c47c
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition: https://arxiv.org/pdf/1406.4729.pdf
R-CNN, Fast R-CNN, Faster R-CNN, YOLO — Object Detection Algorithms: https://towardsdatascience.com/r-cnn-fast-r-cnn-faster-r-cnn-yolo-object-detection-algorithms-36d53571365e
Region of Interest (RoI) pooling: https://towardsdatascience.com/region-of-interest-pooling-f7c637f409af
YOLO, YOLOv2, YOLOv3: https://amrokamal-47691.medium.com/yolo-yolov2-and-yolov3-all-you-want-to-know-7e3e92dc4899
Faster RCNN: https://arxiv.org/pdf/1506.01497.pdf
Mask R-CNN: https://arxiv.org/pdf/1703.06870.pdf
Anchor boxes: https://towardsdatascience.com/anchor-boxes-the-key-to-quality-object-detection-ddf9d612d4f9
Road extraction using ArcGIS API https://developers.arcgis.com/python/sample-notebooks/tabular-data-supervised-learning-using-automl/
Awesome advice on how to train GANs https://www.fast.ai/2019/05/03/decrappify/
AutoML: https://github.com/windmaple/awesome-AutoML
AutoDL: https://github.com/D-X-Y/Awesome-AutoDL