- Online Classes : Keras and Transfer Learning.
- Some Ressources : https://keras.io/layers/advanced-activations/ https://devblogs.nvidia.com/deep-learning-self-driving-cars/ 3.Read about Collabroratory Notebook 4.ELU - activation Function.
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How do I choose an optimizer for my tensorflow model? https://www.quora.com/How-do-I-choose-an-optimizer-for-my-tensorflow-model
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What are good initial weights in a neural network? https://stats.stackexchange.com/questions/47590/what-are-good-initial-weights-in-a-neural-network
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Transfer Learning: How to choose a pre-trained model? https://www.analyticsvidhya.com/blog/2017/06/transfer-learning-the-art-of-fine-tuning-a-pre-trained-model/
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Activation functions and it’s types-Which is better? https://towardsdatascience.com/activation-functions-and-its-types-which-is-better-a9a5310cc8f
- Generator Class in the Pipeline
- Keras - Checkpoints and Callbacks
- Image Augmentation
- Matplotlib For Drawing Insights onj the Train and Validation Dataset.
- Generated the model.h5
- Localization + Classification.
- Sliding window for detecting objects all over the image.(Size of the ppatch depends on the size of the image.).
- Activation Map for detecting objects and classes.
- YOLO : Choose the ground truth of each classes properly.
- Centre block or the grid cell that lies on centre of the object, is responsible for detecting the object.
- YOLO v1 : 1000 classes.
- It treats the image as a single regression problem.
- Five outputs : X, Y, W, H, Confidence.
- Confidence = Pr(Object) * IOU.
- IOU : Intersection over Union.
- IOU tends to be within 0 and 1. It depends ont he overlapping of the images.
- Non-max supression algorithm
- https://medium.com/diaryofawannapreneur/yolo-you-only-look-once-for-object-detection-explained-6f80ea7aaa1e
- Region-based Convolutional Neural Networks
- Mini-YOLO : https://github.com/xslittlegrass/CarND-Vehicle-Detection/blob/master/vehicle%20detection.ipynb
- Objects with the Same center point on the image, Only object can be detected. Changing the size of the sliding window would help to certain level.
- Loss Function in YOLO.
- Pixel Level Detail in Term 3, Image Semantioc Segmentation, Facebook AI research (FAIR).
- SSD vs YOLO
- Mask R-CNN - Classification + segmentation