lixin2002cn

lixin2002cn's Stars

• yiskw713/boundary_loss_for_remote_sensing

  Pytorch re-implementation of boundary loss, proposed in "Boundary Loss for Remote Sensing Imagery Semantic Segmentation"

  Language:Python10113

• huaaaliu/RGBX_Semantic_Segmentation

  Language:Python31730

• a791702141/SSG

  This project is the official implementation of ``Self-Supervised Graph Neural Network for Multi-Source Domain Adaptation'' in PyTorch, which is accepted by ACM MM 2022.

  Language:Python122

• weiyikang/MCC-DA

  "Multi-Source Collaborative Contrastive Learning for Decentralized Domain Adaptation", IEEE TCSVT

  Language:Python1

• bubbliiiing/faster-rcnn-pytorch

  这是一个faster-rcnn的pytorch实现的库，可以利用voc数据集格式的数据进行训练。

  Language:Python1.6k357

• iSEE-Laboratory/VersReID

  (TPAMI2024) Official implementation of Paper ''A Versatile Framework for Multi-scene Person Re-identification''

  Language:Python363

• mariegadeberg/AISOutlierDetection

  Language:Python4

• LeoPits/Vessels-anomaly-detection-with-AIS-data

  Anomaly detection from ships' Automatic Identification System (AIS) data

  Language:Jupyter Notebook6

• JaydenZeng/EMMR

  Mitigating Inconsistencies in Multimodal Sentiment Analysis under Uncertain Missing Modalities, in EMNLP2022

  Language:Python222

• CIA-Oceanix/TrAISformer

  Pytorch implementation of TrAISformer---A generative transformer for AIS trajectory prediction (https://arxiv.org/abs/2109.03958).

  Language:Python11438

• daixinghome/Distill_GID_detectron2

  Language:Python254

• LutingWang/awesome-knowledge-distillation-for-object-detection

  A curated list of awesome knowledge distillation papers and codes for object detection.

  1234

• yyyyangyi/CNNs-for-Multi-Source-Remote-Sensing-Data-Fusion

  Language:Python585

• ai-dawang/PlugNPlay-Modules

  Language:Python2.5k211

• summitgao/WPANet

  基于小波变换平行注意力的多源遥感图像分类，北京航空航天大学学报，2023

  Language:Python212

• walking-shadow/Simple-Remote-Sensing-Change-Detection-Framework

  A simplified implementation of remote sensing change detection based on pytorch

  Language:Python13911

• AnkurDeria/MFT

  Pytorch implementation of Multimodal Fusion Transformer for Remote Sensing Image Classification.

  Language:Jupyter Notebook18920

• xungeer29/Remote-Sensing-Image-Classification

  深度学习图像分类的入门教程

  Language:Python27169

• GatorSense/MUUFLGulfport

  MUUFL Gulfport Hyperspectral and LIDAR Data: This data set includes HSI and LIDAR data, Scoring Code, Photographs of Scene, Description of Data

  Language:Matlab8230

• summitgao/MSFMamba

  Code for "MSFMamba: Multi-Scale Feature Fusion State Space Model for Multi-Source Remote Sensing Image Classification"

  10

• shibing624/nlp-tutorial

  自然语言处理（NLP）教程，包括：词向量，词法分析，预训练语言模型，文本分类，文本语义匹配，信息抽取，翻译，对话。

  Language:Jupyter Notebook40566

• PKU-TANGENT/nlp-tutorial

  NLP新手入门教程

  Language:Python1.1k118

• datawhalechina/self-llm

  《开源大模型食用指南》针对**宝宝量身打造的基于Linux环境快速微调（全参数/Lora）、部署国内外开源大模型（LLM）/多模态大模型（MLLM）教程

  Language:Jupyter Notebook10.1k1.2k

• wangxuqi/Prompt-Engineering-Guide-Chinese

  Prompt工程师指南，源自英文版，但增加了AIGC的prompt部分，为了降低同学们的学习门槛，翻译更新

  Language:MDX1.1k116

• tangjunjun966/cuda-tutorial-master

  第一章 指针篇 第二章 CUDA原理篇 第三章 CUDA编译器环境配置篇 第四章 kernel函数基础篇 第五章 kernel索引(index)篇 第六章 kenel矩阵计算实战篇 第七章 kenel实战强化篇 第八章 CUDA内存应用与性能优化篇 第九章 CUDA原子(atomic)实战篇 第十章 CUDA流(stream)实战篇 第十一章 CUDA的NMS算子实战篇 第十二章 YOLO的部署实战篇 第十三章 基于CUDA的YOLO部署实战篇

  Language:Cuda171

• cxyth/rs-segment.pytorch

  遥感影像语义分割

  Language:Jupyter Notebook437

• Mikoto10032/DeepLearning

  深度学习入门教程, 优秀文章, Deep Learning Tutorial

  Language:Jupyter Notebook14.8k3.6k

• Ding-Kexin/IF_CALC

  The repository contains the implementations for Coupled Adversarial Learning for Fusion Classification of Hyperspectral and LiDAR Data

  Language:Python166

• Alro10/deep-learning-time-series

  List of papers, code and experiments using deep learning for time series forecasting

  Language:Jupyter Notebook2.6k530

• nachi-hebbar/Time-Series-Forecasting-LSTM

  Time series forecasting using LSTM in Python

  Language:Jupyter Notebook88157