There are 7 repositories under residual-networks topic.
Play deep learning with CIFAR datasets
iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press
Wide Residual Networks (WideResNets) in PyTorch
Collection of Keras models used for classification
A PyTorch implementation for PyramidNets (Deep Pyramidal Residual Networks, https://arxiv.org/abs/1610.02915)
Improved Residual Networks (https://arxiv.org/pdf/2004.04989.pdf)
Pytorch code for ICCV'23 paper. NEO 360: Neural Fields for Sparse View Synthesis of Outdoor Scenes
A2S2K-ResNet: Attention-Based Adaptive Spectral-Spatial Kernel ResNet for Hyperspectral Image Classification
Official code for ResUNetplusplus for medical image segmentation (TensorFlow & Pytorch implementation)
Various CNN models for CIFAR10 with Chainer
Torch implementation of the paper "Deep Pyramidal Residual Networks" (https://arxiv.org/abs/1610.02915).
Wide Residual Networks in Keras
Source code of paper: (not available now)
Handwritten digit recognition with MNIST & Keras
Tensorflow - Very Deep Convolutional Neural Networks For Raw Waveforms - https://arxiv.org/pdf/1610.00087.pdf
Official PyTorch implementation of "Artist Style Transfer Via Quadratic Potential"
Tool wear prediction by residual CNN
Meta-Zeta是一个基于强化学习的五子棋(Gobang)模型,主要用以了解AlphaGo Zero的运行原理的Demo,即神经网络是如何指导MCTS做出决策的,以及如何自我对弈学习。源码+教程
Python implementation of "Deep Residual Learning for Image Recognition" (http://arxiv.org/abs/1512.03385 - MSRA, winner team of the 2015 ILSVRC and COCO challenges).
Wide Residual Networks implemented in TensorLayer and TensorFlow.
Keras Implementation Residual Attention Network
Modified Residual U-Net (ResUnet) for Image Segmentation
Deep learning projects including applications (face recognition, neural style transfer, autonomous driving, sign language reading, music generation, translation, speech recognition and NLP) and theories (CNNs, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, hyperparameter tuning, regularization, optimization, Residual Networks). Deep Learning Specialization by Andrew Ng, deeplearning.ai
Deep Learning big homework of UCAS
This library provides a set of basic functions for different type of deep learning (and other) algorithms in C.This deep learning library will be constantly updated
PyTorch implementation of residual networks trained on CIFAR-10 dataset (2017)
✂️ Deep learning-based splice site predictor that improves spliced alignments
Pore-based Fingerprint Recognition System based on Deep Learning Architecture
Caffe implementation of the paper "Deep Pyramidal Residual Networks" (https://arxiv.org/abs/1610.02915).
Unofficial pytorch implementation of ReZero in ResNet