xuchen86's repositories

animegan2-pytorch

PyTorch implementation of AnimeGANv2

Language:Jupyter NotebookLicense:MITStargazers:0Issues:1Issues:0

Awesome-Deep-Camera-Calibration

Deep Learning for Camera Calibration: A Survey

Stargazers:0Issues:0Issues:0

awesome-semantic-segmentation-pytorch

Semantic Segmentation on PyTorch (include FCN, PSPNet, Deeplabv3, Deeplabv3+, DANet, DenseASPP, BiSeNet, EncNet, DUNet, ICNet, ENet, OCNet, CCNet, PSANet, CGNet, ESPNet, LEDNet, DFANet)

Language:PythonLicense:Apache-2.0Stargazers:0Issues:1Issues:0

awesome-transformers-in-medical-imaging

A collection of resources on applications of Transformers in Medical Imaging.

Stargazers:0Issues:1Issues:0

bayesian-neural-network-pytorch

PyTorch implementation of bayesian neural network.

Language:PythonLicense:MITStargazers:0Issues:0Issues:0

Bayesian-Segmentation-and-Uncertainty-estimation-on-CityScapes

Implement a network for semantic segmentation in image data, and also generate estimates of aleatoric and epistemic uncertainties associated with the segmentation.

License:MITStargazers:0Issues:0Issues:0

bayesian-torch

A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch

Language:PythonLicense:BSD-3-ClauseStargazers:0Issues:0Issues:0

BayesianDeepLearning-Survey

Bayesian Deep Learning: A Survey

Stargazers:0Issues:0Issues:0

BayesianUNet

Pytorch Bayesian UNet model for segmentation and uncertainty prediction

License:GPL-3.0Stargazers:0Issues:0Issues:0

BNN-Stock-Predictions

Bayesian Neural Networks for Quantifying Uncertainty and Predicting Stock Fluctuations: A Comparison of LSTMs, GRUs, and Transformers

License:MITStargazers:0Issues:0Issues:0

CroPatho-Leaf-Disease-Detection

CroPatho is an Android Application which can detect diseases on crops by processing the leaf image.

Stargazers:0Issues:0Issues:0

CS-Notes

:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计

Stargazers:0Issues:0Issues:0

DAMO-YOLO

DAMO-YOLO: a fast and accurate object detection method with some new techs, including NAS backbones, efficient RepGFPN, ZeroHead, AlignedOTA, and distillation enhancement.

License:Apache-2.0Stargazers:0Issues:0Issues:0

evidential-deeplearning

Implementation of "Evidential Deep Learning to Quantify Classification Uncertainty" proposing a method to quantify uncertainty in a neural network.

Language:PythonLicense:MITStargazers:0Issues:0Issues:0

Hierarchical-Bayesian-Defense

Official PyTorch Implementation for Towards Adversarial Robustness of Bayesian Neural Network through Hierarchical Variational Inference (Openreview)

Language:PythonStargazers:0Issues:1Issues:0

Image-Recognition-system

✨基于 3D 卷积神经网络(CNN)的阿尔兹海默智能诊断 Web 应用 Alzheimer's Intelligent Diagnosis Web Application based on 3D Convolutional Neural Network and the ADNI Dataset ✨ 🚩(with README in English) 📌含在线demo:医学影像识别系统,图像识别可视化界面,OCR,快速部署深度学习模型为网页应用,Web预测系统,决策支持系统(DSS),图像识别前端网页,图像识别Demo展示-Pywebio。AI人工智能图像识别-Pytorch;nii医学影像处理;ADNI数据集。100%纯Python代码,轻量化,易复现

License:MITStargazers:0Issues:0Issues:0

leetcode-master

《代码随想录》LeetCode 刷题攻略:200道经典题目刷题顺序,共60w字的详细图解,视频难点剖析,50余张思维导图,支持C++,Java,Python,Go,JavaScript等多语言版本,从此算法学习不再迷茫!🔥🔥 来看看,你会发现相见恨晚!🚀

Stargazers:0Issues:1Issues:0

MaxSquareLoss

Code for "Domain Adaptation for Semantic Segmentation with Maximum Squares Loss" in PyTorch.

Language:PythonLicense:MITStargazers:0Issues:0Issues:0

mmsegmentation

OpenMMLab Semantic Segmentation Toolbox and Benchmark.

Language:PythonLicense:Apache-2.0Stargazers:0Issues:0Issues:0

multitask-seg-depth

Multi Task Learning for Semantic Segmentation, Instance Segmentation and Depth Estimation

Language:PythonLicense:MITStargazers:0Issues:0Issues:0
Language:PythonLicense:Apache-2.0Stargazers:0Issues:1Issues:0

objectdetection_script

一些关于目标检测的脚本的改进思路代码,详细请看readme.md

Stargazers:0Issues:0Issues:0

ONNX-YOLOv8-Object-Detection

Python scripts performing object detection using the YOLOv8 model in ONNX.

Language:PythonLicense:MITStargazers:0Issues:0Issues:0

Plant-Disease-Detection

Plant Disease Detection is one of the mind-boggling issues when we talk about using Technology in Agriculture. Although researches have been done to detect whether a plant is healthy or diseased using Deep Learning and with the help of Neural Network, new techniques are still being discovered. For Fewer Data Classical Machine Learning Models are s

Stargazers:0Issues:0Issues:0

Retinal-Blood-Vessels-Segmentation-and-Denoising

A Morphological Hessian Based Approach for Retinal Blood Vessels Segmentation and Denoising Using Region-Based Otsu Thresholding

License:MITStargazers:0Issues:0Issues:0

Retinal-Vessel-Segmentation-using-variants-of-UNET

Retinal vessel segmentation using U-NET, Res-UNET, Attention U-NET, and Residual Attention U-NET (RA-UNET)

Stargazers:0Issues:0Issues:0

RPNODE_FSS

Improving Adversarial Robustness for Few Shot Segmentation with Regularized Neural-ODEs

Language:PythonLicense:MITStargazers:0Issues:0Issues:0

VesselSeg-Pytorch

Retinal vessel segmentation toolkit based on pytorch

Language:PythonLicense:Apache-2.0Stargazers:0Issues:1Issues:0
Language:PythonStargazers:0Issues:0Issues:0