Official repository of my book: "Deep Learning with PyTorch Step-by-Step: A Beginner's Guide"
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Updated
May 10, 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.
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)
Coarse-to-Fine CNN for Image Super-Resolution (IEEE Transactions on Multimedia,2021)
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.
Facial analysis framework for genetic disorders with facial dysmorphism
Genre Classification using Convolutional Neural Networks
Deep Learning Projects using Python & Pytorch
Enhanced CNN for image denoising (CAAI Transactions on Intelligence Technology, 2019)
Udacity AI for Healthcare Nanodegree Project: Measurement of Hippocampus Structure in MRI 3-D Images using Deep Learning Image Segmentation
Attention-guided CNN for image denoising(Neural Networks,2020)
Pytorch Tutorial Notebooks
Designing and Training of A Dual CNN for Image Denoising (Knowledge-based Systems, 2021)
Implementation of Convolutional Neural Networks for Sentence Classification by Yoon Kim
Official repo for the following paper: Traffic Forecasting on New Roads Unseen in the Training Data Using Spatial Contrastive Pre-Training (SCPT) (ECML PKDD DAMI '23)
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