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12306

12306智能刷票，订票

analytics_vidhya

Codes related to activities on AV including articles, hackathons and discussions.

cadlab

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory

ce-net

The manuscript has been accepted in TMI.

cvpr2021-paper-code-interpretation

cvpr2021/cvpr2020/cvpr2019/cvpr2018/cvpr2017 论文/代码/解读/直播合集，极市团队整理

deeplearning-in-action

《深度学习原理与实践》相关代码——source code of the book <deep learning in action>

deformable-convnets

Deformable Convolutional Networks

delta

DELTA is a deep learning based natural language and speech processing platform.

dive-into-dl-pytorch

本项目将《动手学深度学习》（Dive into Deep Learning）原书中的MXNet代码实现改为PyTorch实现。

dlwpt-code

Code for the book Deep Learning with PyTorch by Eli Stevens and Luca Antiga.

egnet

EGNet:Edge Guidance Network for Salient Object Detection (ICCV 2019)

elitequant

A list of online resources for quantitative modeling, trading, portfolio management

fcn.berkeleyvision.org

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.

fullnet-varce

Pytorch implementation of FullNet-varCE

kg_instance_segmentation

Multi-scale Cell Instance Segmentation with Keypoint Graph based Bounding Boxes

labelme

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

libpku

贵校课程资料民间整理

medical-imaging-datasets

A list of Medical imaging datasets.

opencv

Open Source Computer Vision Library

opencv_exercises

opencv python exercises

partiallyreversibleunet

py12306

🚂 12306 购票助手，支持集群，多账号，多任务购票以及 Web 页面管理

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

pytorch_tutorial

《Pytorch模型训练实用教程》中配套代码

sjtu-courses

上海交通大学课程资料分享

stnbhwd

Modules for spatial transformer networks (BHWD layout)

tianchi-medical-lungtumordetect

天池医疗AI大赛[第一季]：肺部结节智能诊断 UNet/VGG/Inception/ResNet/DenseNet

torch7

http://torch.ch

unet

unet for image segmentation

using-deep-learning-neural-networks-and-candlestick-chart-representation-to-predict-stock-market