qingfenghcy's Stars
bai-shang/crnn_ctc_ocr_tf
Extremely simple implement for CRNN by Tensorflow
guiyang882/DL.EyeSight
Mainly use SSD, YOLO and other models to solve the target detection problem in image and video !
skrish13/PyTorch-mask-x-rcnn
PyTorch implementation of the Mask-X-RCNN network proposed in the 'Learning to Segment Everything' paper by Facebook AI Research
wucng/TensorExpand
集成包
WarBean/hyperboard
A web-based dashboard for Deep Learning
Kaggle/kaggle-api
Official Kaggle API
matterport/Mask_RCNN
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
sergiomsilva/alpr-unconstrained
License Plate Detection and Recognition in Unconstrained Scenarios
hoya012/deep_learning_object_detection
A paper list of object detection using deep learning.
floodsung/Deep-Learning-Papers-Reading-Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
YIYIMZ/my_orc_keras_verification_code_identification
本项目实现了ocr主流算法gru/lstm+ctc+cnn架构,进行不定长度验证码识别,达到不分割字符而识别验证码内容的效果。验证码内容包含了大小字母以及数字,并增加点、线、颜色、位置、字体等干扰项。本项目对gru +ctc+cnn、lstm+ctc+cnn、cnn三种架构进行了对比,实践说明同等训练下gru/lstm+ctc+cnn架构准确率和速度均明显优于cnn架构,gru +ctc+cnn优于lstm+ctc+cnn,在实验2500个样本数据200轮训练时,gru +ctc+cnn架构在500样本测试准确率达90.2%。本项目技术能够训练长序列的ocr识别,更换数据集和相关调整,即可用于比如身份证号码、车牌、手机号、邮编等识别任务,也可用于汉字识别。
facebookresearch/Detectron
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
ethanhe42/softer-NMS
Bounding Box Regression with Uncertainty for Accurate Object Detection (CVPR'19)
xiaochus/YOLOv3
Keras implementation of yolo v3 object detection.
titu1994/Keras-NASNet
"NASNet" models in Keras 2.0+ with weights
AIChallenger/AI_Challenger_2018
AI Challenger, a platform for open datasets and programming competitions to artificial intelligence (AI) talents around the world. https://challenger.ai/
bobo0810/XueLangTianchi
雪浪制造AI挑战赛—视觉计算辅助良品检测
junyanz/pytorch-CycleGAN-and-pix2pix
Image-to-Image Translation in PyTorch
dive-into-machine-learning/dive-into-machine-learning
Free ways to dive into machine learning with Python and Jupyter Notebook. Notebooks, courses, and other links. (First posted in 2016.)
Sanster/text_renderer
Generate text images for training deep learning ocr model
LianHaiMiao/pytorch-lesson-zh
pytorch 包教不包会
linrongc/youtube-8m
Code of PhoenixLin(3rd place) in the 2nd Youtube8M Video Understanding Challenge
lightfate/XueLang-YOLOhasst
雪浪制造AI挑战赛—视觉计算辅助良品检测 test_a 952 test_b 953
miha-skalic/youtube8mchallenge
1st place solution to Kaggle's 2018 YouTube-8M Video Understanding Challenge
google-deepmind/kinetics-i3d
Convolutional neural network model for video classification trained on the Kinetics dataset.
facebookresearch/video-nonlocal-net
Non-local Neural Networks for Video Classification
jeffreyyihuang/two-stream-action-recognition
Using two stream architecture to implement a classic action recognition method on UCF101 dataset
pytorch/examples
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
chiphuyen/stanford-tensorflow-tutorials
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
andy-yun/pytorch-0.4-yolov3
Yet Another Implimentation of Pytroch 0.4.1 and YoloV3 on python3