Python - 100天从新手到大师

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

Graph Transformer Networks (Authors' PyTorch implementation for the NeurIPS 19 paper)

A multi-task learning example for the paper https://arxiv.org/abs/1705.07115

爬虫+数据分析实战项目

Brain Tumor Segmentation done using U-Net Architecture.

[NeurIPS'22] Multi-Granularity Cross-modal Alignment for Generalized Medical Visual Representation Learning

Retinal Vessel Segmentation using U-Net architecture. DRIVE and STARE datasets are used.

This is the repository for the paper "2D Medical Image Synthesis Using Transformer-based Denoising Diffusion Probabilistic Model".

Superpixel-based Graph Convolutional Network for Semantic Segmentation

An education step by step implementation of SimCLR that accompanies the blogpost

GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in COVID-19 Classification

本项目整理了Google 5天AI智能体课程的学习成果，涵盖Gemini API、LangChain等核心技术从基础到多智能体系统的完整实践。课程系统化教授智能体架构、工具调用、推理规划、记忆管理和多智能体协作，帮助开发者掌握构建自主AI智能体的全流程技能。提供中英文双语文档和代码示例，适合有Python基础的开发者。

Stroke-GFCN: segmentation of Ischemic brain lesions

Wav2Lip简明教程&Wav2Lip快速入门