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2021-cv-surveys

2021 年，计算机视觉相关综述。包括目标检测、跟踪........

automatic_ticket_purchase

大麦网抢票脚本

bayesian-networks-in-python

🧮 Bayesian networks in Python

bronchinet

Airway segmentation from chest CTs using deep Convolutional Neural Networks

causal-reasoning-in-probability-trees

causalml

The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalML

ccbanet

CCBANet: Cascading Context and Balancing Attention for Polyp Segmentation

chatpaper

Use ChatGPT to summarize the arXiv papers. 全流程加速科研，利用chatgpt进行论文全文总结+专业翻译+润色+审稿+审稿回复

ct-lung-segment

Algorithms for lung contour segmentation, lung trachea segmentation and pulmonary blood vessel segmentation based on CT images.

cvpr2022-paper-code-interpretation

cvpr2022/cvpr2021/cvpr2020/cvpr2019/cvpr2018/cvpr2017 论文/代码/解读/直播合集，极市团队整理

dataaugmentation_forobjectdetect

本仓库主要包含了针对目标检测数据集的增强手段和源码：图像的旋转，镜像，裁剪，亮度/对比度的变换等

deep-forest

An Efficient, Scalable and Optimized Python Framework for Deep Forest (2021.2.1)

deep_learning_regression

deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

easylearn_dev

Easylearn is designed for machine learning mainly in resting-state fMRI, radiomics and other fields (such as EEG). Easylearn is built on top of scikit-learn, pytorch and other packages. Easylearn can assist doctors and researchers who have limited coding experience to easily realize machine learning, e.g., (MR/CT/PET/EEG)imaging-marker- or other bi

econml

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

feature_selection

gcn

Implementation of Graph Convolutional Networks in TensorFlow

lung-segmentation-project

This project uses a process known as segmentation to extract individual lung components from CT scans such as the airway, bronchioles, outer lung structure, and cancerous growths. Mathematical descriptions of these objects can be used for AI research, such as predicting benign vs malignant tumors to prevent unnecessary and invasive cancer treatments, early recognition of tumors, and modeling the growth rate of tumors.

lungmask

Automated lung segmentation in CT

machine_learning_python

关于机器学习的相关方法汇总

machinelearning_python

机器学习算法python实现

msnet

(MICCAI 2021) Automatic Polyp Segmentation via Multi-scale Subtraction Network

n4biasfieldcorrection

This is N4 bias field correction for MRI

paper-reading

深度学习经典、新论文逐段精读

pybn

Bayesian Networks in Python

pygcn

Graph Convolutional Networks in PyTorch

pytorch-entity-embedding-dnn-regressor

A Pytorch implementation of a DNN regressor based on Entity Embedding which is applicable to datasets containing categorical features

ra-gcn

Implementation code of RA-GCN: Graph Convolutional Network for Disease Prediction Problems with Imbalanced Data accepted by Medical Image Analysis Journal

sanet

Codes for MICCAI2021 paper "Shallow Attention Network for Polyp Segmentation"