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

Multimodal Hyperspectral Unmixing: Insights from Attention Networks, IEEE TGRS, 2022

The code of paper "UADNet: A Joint Unmixing and Anomaly Detection Network Based on Deep Clustering for Hyperspectral Image" in TGRS 2024.

Rev-Net: A Reversible Generative Network for Hyperspectral Unmixing with Spectral Variability

Zhu Han, Jin Yang, Lianru Gao, Zhiqiang Zeng, Bing Zhang, Jocelyn Chanussot. Dual-Branch Subpixel-Guided Network for Hyperspectral Image Classification, IEEE TGRS, 2024

demo of DAAN

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…

[ECCV2024] An official pytorch implement of the paper "MambaIR: A simple baseline for image restoration with state-space model".

Simple, minimal implementation of the Mamba SSM in one file of PyTorch.

[SLT'24] The official implementation of SSAMBA: Self-Supervised Audio Representation Learning with Mamba State Space Model

Code Implementation of EfficientVMamba

[ICML 2024] Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

基于深度学习的肿瘤辅助诊断系统，以图像分割为核心，利用人工智能完成肿瘤区域的识别勾画并提供肿瘤区域的特征来辅助医生进行诊断。有完整的模型构建、后端架设、工业级部署和前端访问功能。TensorRT、PyTorch 、OpenCV 、Flask、Vue

🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

Code for hyperspectral unmixing

Code for ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks

Shuaikai Shi, Min Zhao, Lijun Zhang, Yoann Altmann and Jie Chen, "Probabilistic Generative Model for Hyperspectral Unmixing Accounting for Endmember Variability," in IEEE Transactions on Geoscience…

Danfeng Hong, Lianru Gao, Jing Yao, Naoto Yokoya, Jocelyn Chanussot, Uta Heiden, Bing Zhang. Endmember-Guided Unmixing Network (EGU-Net): A General Deep Learning Framework for Self-Supervised Hyper…

Resource collection for the paper "Integration of Physics-Based and Data-Driven Models for Hyperspectral Image Unmixing: A summary of current methods" (SPM 2023).

Spectral unmixing using deep generative models

Minimum-volume constrained non-negative matrix factorisation, adapted into Python from L. Miao and H. Qi, "Endmember Extraction From Highly Mixed Data Using Minimum Volume Constrained Nonnegative M…