Official repository of my book: "Deep Learning with PyTorch Step-by-Step: A Beginner's Guide"
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Updated
Apr 14, 2024 - Jupyter Notebook
Official repository of my book: "Deep Learning with PyTorch Step-by-Step: A Beginner's Guide"
Pytorch Tutorial, Pytorch with Google Colab, Pytorch Implementations: CNN, RNN, DCGAN, Transfer Learning, Chatbot, Pytorch Sample Codes
Lightweight Image Super-Resolution with Enhanced CNN (Knowledge-Based Systems,2020)
📦 PyTorch based visualization package for generating layer-wise explanations for CNNs.
Coarse-to-Fine CNN for Image Super-Resolution (IEEE Transactions on Multimedia,2021)
Attention-guided CNN for image denoising(Neural Networks,2020)
Implementation of MobileNetV3 in pytorch
This repository contains the architectures, Models, logs, etc pertaining to the SimpleNet Paper (Lets keep it simple: Using simple architectures to outperform deeper architectures )
Asymmetric CNN for image super-resolution (IEEE Transactions on Systmes, Man, and Cybernetics: Systems 2021)
Enhanced CNN for image denoising (CAAI Transactions on Intelligence Technology, 2019)
Designing and Training of A Dual CNN for Image Denoising (Knowledge-based Systems, 2021)
Genre Classification using Convolutional Neural Networks
Binary classification problem that aims to classify human voices from audio recordings. Implemented using PyTorch and Librosa.
In this project, we propose a CNN model to classify single-channel EEG for driver drowsiness detection. We use the Class Activation Map (CAM) method for visualization. Results show that the model not only has a high accuracy but also learns biologically explainable features, e.g., Alpha spindles and Theta burst, as evidence for the drowsy state.
1D convolutional neural networks for activity recognition in python.
Code for "Deep Learning Based EDM Subgenre Classification using Mel-Spectrogram and Tempogram Features" arXiv:2110.08862, 2021.
online early forest fire detection system based on drone platform.
Class to automatic create Convolutional Neural Network in PyTorch
A suite of Python scripts allowing the end-user to use Deep Learning to detect objects in georeferenced raster images.
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