633 Open source projects that are alternatives of or similar to Human Action Recognition With Keras

Be Driven 🚘

1st place solution

CNN image classifier implemented in Keras Notebook 🖼️.

Text to Speech with PyTorch (English and Mongolian)

A binary library for very fast face detection using compact CNNs.

Object classification with CIFAR-10 using transfer learning

Lung fields segmentation on CXR images using convolutional neural networks.

The repository provides usefull python scripts for ML and data analysis

Crack detection for an autonomous UAV

A CoreML model which classifies images of food

easy convolution neural network

Experimental codes for paper "Outer Product-based Neural Collaborative Filtering".

Implementations of some popular Saliency Maps in Keras

Credit card fraud detection through logistic regression, k-means, and deep learning.

Reproduce CheXNet

Kaggle Data Science Bowl 2018

Identifying people from small audio fragments

All Convolutional Network: (https://arxiv.org/abs/1412.6806#) implementation in Keras

MR-CNNs for Large-Scale Scene Recognition

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S. Su, M. Delbracio, J. Wang, G. Sapiro, W. Heidrich, O. Wang. Deep Video Deblurring. CVPR 2017, Spotlight

A Neural Networking library based on NumPy only

Pytorch Imagenet Models Example + Transfer Learning (and fine-tuning)

Kaggle Kernel for House Prices competition https://www.kaggle.com/massquantity/all-you-need-is-pca-lb-0-11421-top-4

SHAInet - a pure Crystal machine learning library

a collection of my notes on deep learning

深度学习与PyTorch入门实战视频教程 配套源代码和PPT

ResNet with Shift, Depthwise, or Convolutional Operations for CIFAR-100, CIFAR-10 on PyTorch

Efficient Sparse-Winograd Convolutional Neural Networks (ICLR 2018)

Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine

🙈A PyTorch implementation of the paper "Visualizing and Understanding Convolutional Networks." （ECCV 2014)

Assignment solutions for the CS231n course taught by Stanford on visual recognition. Spring 2017 solutions are for both deep learning frameworks: TensorFlow and PyTorch.

Quantization of Convolutional Neural networks.

DensePoint: Learning Densely Contextual Representation for Efficient Point Cloud Processing (ICCV 2019)

A curated list of Deep Learning resources sorted by reputation

实现常用基于深度学习的人脸检测算法

Semi-Supervised Video Object Segmentation (VOS) with Tensorflow. Includes implementation of *MaskRNN: Instance Level Video Object Segmentation (NIPS 2017)* as part of the NIPS Paper Implementation Challenge.

Using Machine Learning to predict the type of exercise from movement data

Implementation of Convolutional Neural Networks for Sentence Classification (Y.Kim, EMNLP 2014) on Pytorch.

An Embedded Computer Vision & Machine Learning Library (CPU Optimized & IoT Capable)

[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow

Set of scripts and data for reproducing dog breed classification model training, analysis, and inference.

Code for Kaggle Competitions

CV backbones including GhostNet, TinyNet and TNT, developed by Huawei Noah's Ark Lab.

Important paper implementations for Question Answering using PyTorch

Finding Tiny Faces in PyTorch

A neural network to generate captions for an image using CNN and RNN with BEAM Search.

A fully convolution-network for speech-to-text, built on pytorch.

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

记录我学习数据挖掘过程的笔记和见到的奇技，持续更新～

[ECCV 2018] Sparsely Aggreagated Convolutional Networks https://arxiv.org/abs/1801.05895

A searchable compilation of Kaggle past solutions

Code for the paper Benchmark Analysis of Representative Deep Neural Network Architectures

Comparison tools

convolutional lstm implementation in pytorch

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[CVPR19] DeepCO3: Deep Instance Co-segmentation by Co-peak Search and Co-saliency (Oral paper)

TensorFlow implementation of AlexNet and its training and testing on ImageNet ILSVRC 2012 dataset

Udacity Self-Driving Car Engineer Nanodegree projects.

Timeception for Complex Action Recognition, CVPR 2019 (Oral Presentation)