liuzm07

liuzm07's Stars

• roncoo/roncoo-pay

  龙果支付系统（roncoo-pay）是国内首款开源的互联网支付系统，拥有独立的账户体系、用户体系、支付接入体系、支付交易体系、对账清结算体系。目标是打造一款集成主流支付方式且轻量易用的支付收款系统，满足互联网业务系统打通支付通道实现支付收款和业务资金管理等功能。

  Language:Java4.9k2.6k

• didi/tinyid

  ID Generator id生成器 分布式id生成系统，简单易用、高性能、高可用的id生成系统

  Language:Java2.3k586

• codedrinker/community

  开源论坛、问答系统，现有功能提问、回复、通知、最新、最热、消除零回复功能。功能持续更新中…… 技术栈 Spring、Spring Boot、MyBatis、MySQL/H2、Bootstrap

  Language:Java2.7k783

• AIGC-Audio/AudioGPT

  AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head

  Language:Python10.1k868

• koishijs/novelai-bot

  Generate images by NovelAI | 基于 NovelAI 的画图机器人

  Language:TypeScript2.5k207

• shengxinjing/self-employed-workbook

  写给自己的程序员自由职业工作手册

  39514

• JosephZhu1983/java-common-mistakes

  书籍《Java 开发坑点解析：从根因分析到最佳实践》 & 极客时间专栏《Java业务开发常见错误100例》源码

  Language:Java1.8k721

• AbaK1r/FasterRcnnWithAttention

  Language:Python52

• shenhangcs/swin-transformer-faster-rcnn

  Language:Python131

• yangbingjie/DeepCompression-PyTorch

  PyTorch implementation of 'Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding' by Song Han, Huizi Mao, William J. Dally

  Language:Python102

• xinyaoliu/Deep-Compression-for-Neural-Networks

  Deep Compression: Compressing Deep Neural Networks With Pruning, Trained Quantization And Huffman Coding

  Language:Python155

• bemova/Deep-Compression-Compressing-Deep-Neural-Networks-with-Pruning-Trained-Quantization-and-Huffman

  It is a pytorch implementation of https://arxiv.org/abs/1510.00149 paper.

  Language:Python2811

• mightydeveloper/Deep-Compression-PyTorch

  PyTorch implementation of 'Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding' by Song Han, Huizi Mao, William J. Dally

  Language:Python417112

• zhongqiangwu960812/AI-RecommenderSystem

  该仓库尝试整理推荐系统领域的一些经典算法模型

  Language:Jupyter Notebook1.8k388

• SeokHeel/YOLOv3_partitioned_model_with_feature_map_compression

  Language:Python7

• limuhit/ImageCompression

  This is the codes for paper "Learning Convolutional Networks for Content-weighted Image Compression"

  Language:Python7121

• anovaguerrero/Panoramic-BlitzNet

  Deep neural network for object detection and semantic segmentation on indoor panoramic images. The implementation is based on the papers: "What’s in my Room? Object Recognition on Indoor Panoramic Images" and "BlitzNet: A Real-Time Deep Network for Scene Understanding"

  Language:Python186

• AlphaJia/pytorch-faster-rcnn

  pytorch based implementation faster rcnn

  Language:Python44486

• Eniac-Xie/faster-rcnn-resnet

  ResNet Implementation for Faster-rcnn

  Language:Python207117

• bubbliiiing/faster-rcnn-pytorch

  这是一个faster-rcnn的pytorch实现的库，可以利用voc数据集格式的数据进行训练。

  Language:Python1.6k357

• uoip/SSD-variants

  PyTorch implementation of several SSD based object detection algorithms.

  Language:Python24056

• shuyucool/U-net-segmentation

  image segmentation / object detection / keras

  Language:Python4111

• tensorflow/models

  Models and examples built with TensorFlow

  Language:Python77.3k45.8k

• dvornikita/blitznet

  Deep neural network for object detection and semantic segmentation in real-time. Official code for the paper "BlitzNet: A Real-Time Deep Network for Scene Understanding"

  Language:Python313109

• warmspringwinds/pytorch-segmentation-detection

  Image Segmentation and Object Detection in Pytorch

  Language:Jupyter Notebook748169

• TannerGilbert/MaskRCNN-Object-Detection-and-Segmentation

  Train your own custom MaskRCNN Object Detection and Instance Segmentation model.

  Language:Jupyter Notebook6125

• HRNet/HigherHRNet-Human-Pose-Estimation

  This is an official implementation of our CVPR 2020 paper "HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation" (https://arxiv.org/abs/1908.10357)

  Language:Python1.4k272

• HRNet/HRNet-Image-Classification

  Train the HRNet model on ImageNet

  Language:Python971216

• HRNet/HRNet-Object-Detection

  Object detection with multi-level representations generated from deep high-resolution representation learning (HRNetV2h). This is an official implementation for our TPAMI paper "Deep High-Resolution Representation Learning for Visual Recognition". https://arxiv.org/abs/1908.07919

  Language:Python64696

• HRNet/HRNet-Semantic-Segmentation

  The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919

  Language:Python3.2k692