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custom-layers

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Ankit-Kumar-Saini / Coursera_TensorFlow_Advanced_Techniques_Specialization

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Used the Functional API to built custom layers and non-sequential model types in TensorFlow, performed object detection, image segmentation, and interpretation of convolutions. Used generative deep learning including Auto Encoding, VAEs, and GANs to create new content.

object-detection image-segmentation generative-adversarial-networks auto-encoders saliency-map mask-rcnn variational-autoencoders coursera-specialization retina-net model-interpretability tensorflow2 functional-api custom-model-development custom-loss-functions gradcam-visualization custom-layers gradient-tape-optimization custom-training-loops
  • Updated Jun 9, 2021
  • Jupyter Notebook

jElhamm / Article-Deep-Learning-for-the-Gaussian-Wiretap-Channel

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Simulations for the paper "Deep Learning for the Gaussian Wiretap Channel by Rick Fritschek, Rafael F. Schaefer, Gerhard Wunder"

python training deep-learning tensorflow numpy jupyter-notebook optimizer pandas scipy simulations deep-learning-papers loss wiretap encoder-decoder-model matplotlib-pyplot data-communications custom-layers paper-simulations tensorflow-keras-model sklearn-preprocessing
  • Updated Jun 20, 2024
  • Jupyter Notebook

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