Easily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood.

Play deep learning with CIFAR datasets

Deep Xi: A deep learning approach to a priori SNR estimation implemented in TensorFlow 2/Keras. For speech enhancement and robust ASR.

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

Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition (https://arxiv.org/pdf/2006.11538.pdf)

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)

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

Handwritten digit recognition with MNIST & Keras

Tensorflow - Very Deep Convolutional Neural Networks For Raw Waveforms - https://arxiv.org/pdf/1610.00087.pdf

Tool wear prediction by residual CNN