sunnyue123

sunnyue123's Stars

• Candy-CY/Hyperspectral-Image-Classification-Models

  收录及复现的高光谱遥感图像分类模型

  Language:Python5434970

• eecn/Hyperspectral-Classification

  Hyperspectral-Classification Pytorch

  Language:Python5021227156

• nshaud/DeepHyperX

  Deep learning toolbox based on PyTorch for hyperspectral data classification.

  Language:Python4341549122

• danfenghong/IEEE_TPAMI_SpectralGPT

  Hong, D., Zhang, B., Li, X., Li, Y., Li, C., Yao, J., Yokoya, N., Li, H., Ghamisi, P., Jia, X., Plaza, A. and Gamba, P., Benediktsson, J., Chanussot, J. (2024). SpectralGPT: Spectral remote sensing foundation model. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024. DOI:10.1109/TPAMI.2024.3362475.

  Language:Python17552518

• sai-bi/ImageSmoothing

  A collection of image smoothing algorithms.

  Language:C15414165

• WHU-Sigma/HyperSIGMA

  The official repo for the paper "HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation Model"

  Language:Python1284912

• Z-Zheng/FreeNet

  FPGA: Fast Patch-Free Global Learning Framework for Fully End-to-End Hyperspectral Image Classification (TGRS 2020) https://ieeexplore.ieee.org/document/9007624

  Language:Python1014630

• ShuGuoJ/GiGCN

  Language:Python63496

• wliusjtu/Generalized-Smoothing-Framework

  This is the released code for the following papers: A generalized framework for edge-preserving and structure-preserving image smoothing. Liu W, et al., TPAMI 2021, AAAI 2020

  Language:MATLAB442215

• KevinPatel04/Digital-Image-Processing

  This Repository demonstrates how can one apply various image pre-processing, image processing & image post-processing techniques in MATLAB environment.

  Language:MATLAB25204

• senjia1980/FG-SuULDA

  The code of the paper "Flexible Gabor-based Superpixel-level Unsupervised LDA for Hyperspectral Image Classification".

  Language:MATLAB156

• jlowenz/rrwm

  Reweighted Random Walk Matching (RRWM) code repository from http://cv.snu.ac.kr/research/~RRWM/

  Language:Matlab142

• yossidoctor/AI-Traffic-Lights-Controller

  Using reinforcement learning and genetic algorithms to improve traffic flow and reduce vehicle waiting times in a single-lane two-way junction simulator by coordinating traffic signal schedules.

  Language:Python14306

• BBreakWord/CL-MGNet

  Language:Python10111

• laprf/DSTC

  Code for Dual-stage Hyperspectral Image Classification Model with Spectral Supertoken, ECCV 2024

  Language:Python10221

• pratikgirigoswami/Exemplar-Based-Image-Inpainting

  • Image inpainting is the process of seamlessly filling in holes of arbitrary topology in an image to preserve its overall continuity. It is an ancient art of fixing accidental damage and recreating lost information. • Object removal or modification in the original images can be carried out through image inpainting methods. • In this project, various algorithms of Partial Derivative Equation based and Exemplar-based families have been studied and implemented. Results using Total Variation (TV) and Curvature Driven Diffusion (CDD) methods show that CDD produces a better visual quality of results. However, it fails to restore texture information. • To solve this problem, Exemplar-based algorithms are studied and implemented. Traditionally, the data term present in this algorithm is based on the strength of the isophote found using the gradient. The problem with the gradient operator is studied, and a better contour preserving data term is proposed. The proposed data term uses the strength of structure line found using Infinite size Symmetric Exponential Filter (ISEF). This filter helps overcome the drawback of which overcomes the drawback of insensibility to noise and precision of edge localization present in traditional data term. • Results are compared by quantitative analysis using PSNR, SSIM, and FSIM. Subjective analysis is done using Mean Opinion Score. It is proved that the proposed method produces better visual results compared to few other existing exemplar-based methods. • Methods/Keywords: Exemplar-based Image Inpainting, PDE-based Image Inpainting, ISEF Filter, Priority Computation, Isophote, Curvature Driven Diffusion • Software/Tools/Programming Language Used: MATLAB, C

  Language:MATLAB102

• Hang-Fu/NGNMF-E2DSSA

  A Novel Band Selection and Spatial Noise Reduction Method for Hyperspectral Image Classification, TGRS, 2022

  Language:MATLAB9100

• tulilin/S2HM2

  S2HM2: A Spectral-Spatial Hierarchical Masked Modeling Framework for Self-Supervised Feature Learning and Classification of Large-Scale Hyperspectral Images

  Language:Python9200

• danfenghong/IEEE_TGRS_ExViT

  Yao, Jing, Bing Zhang, Chenyu Li, Danfeng Hong, and Jocelyn Chanussot. "Extended vision transformer (ExViT) for land use and land cover classification: A multimodal deep learning framework." IEEE Transactions on Geoscience and Remote Sensing, 2023..

  Language:Python800

• xurui-joei/DBCTNet

  The pytorch implement of DBCTNet

  Language:Python80

• Cimy-wang/KNNRS-HSIC

  Code for KNN-based Representation of Superpixels for hyperspectral image classification

  Language:MATLAB6102

• SUPERMAN123000/IDA-SiamNet

  This is a PyTorch implementation of the paper IDA-SiamNet: Interactive- and Dynamic-Aware Siamese Network for Building Change Detection

  Language:Python621

• zhaoxile/Mixed-Noise-Removal-in-Hyperspectral-Image-via-Low-Fibered-Rank-Regularization

  code of Mixed Noise Removal in Hyperspectral Image via Low-Fibered-Rank Regularization

  Language:MATLAB6102

• ckn3/SA-Recon

  Shape-adaptive Reconstruction

  Language:MATLAB4100

• zh460045050/DRW

  This is the official code of our paper: Dynamic Random Walk for Superpixel Segmentation

  Language:C++41

• zh460045050/ENCut_RWRT

  The official code of the paper: Explored Normalized Cut with Random Walk Refining Term for Image Segmentation

  Language:MATLAB3101

• ZhaohuiXue/TLRSR-IDL

  A DEMO for "Incremental Dictionary Learning-Driven Tensor Low-Rank and Sparse Representation for Hyperspectral Image Classification" (Xue et al., TGRS, 2022)

  Language:MATLAB3101

• aichou233/M3FuNet

  M3FuNet--IEEE TGRS2024

  Language:C++22

• yab-tad/Intelliget-Traffic-Light-Control-System

  A Computer Vision model that uses object detection algorithms and scheduling algorithm to count the number of vehicles in a car lane and controlled traffic lights to minimize wait times.

  Language:Python2

• priyanshu-sharma/INTELLIGENT_TRAFFIC_LIGHT_SCHEDULING_USING_LINEAR_REGRESSION_MODEL

  Language:Jupyter Notebook10