A PyTorch Library for Hyperspectral Image Models: Technical Report

arXiv:2609.39871 · cs.CV · Submitted 2026-09-30 · Read on arXiv

cs.CV

Submitted: 2026-09-30

Updated: 2026-10-07

Code: https://github.com/Tanishq251/Hyperspectral-Image-Models

Terminology

• Transformer — 53× in this paper · explained in 2 episodes
• Benchmark — 47× in this paper · explained in 2 episodes
• Accuracy — 45× in this paper · explained in 1 episode
• Adaptation — 13× in this paper · explained in 1 episode
• Benchmarking — 11× in this paper · explained in 3 episodes
• Provenance — 8× in this paper · explained in 3 episodes
• Adam — 7× in this paper · explained in 2 episodes
• Core — 6× in this paper · explained in 2 episodes
• Data Fusion — 3× in this paper · explained in 3 episodes
• Abstraction — 2× in this paper · explained in 1 episode
• Adversarial Attacks — 2× in this paper · explained in 1 episode
• Aggregation — 2× in this paper · explained in 1 episode
• Conference on Computer Vision and Pattern Recognition — 2× in this paper
• Failure Modes — 2× in this paper · explained in 3 episodes
• Mars Reconnaissance Orbiter — 2× in this paper
• Attention Mechanism — 1× in this paper · explained in 2 episodes
• Compact Reconnaissance Imaging Spectrometer for Mars — 1× in this paper
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Edge Deployment — 1× in this paper · explained in 2 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• Few-Shot Learning — 1× in this paper · explained in 4 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Graph Construction — 1× in this paper · explained in 3 episodes
• IEEE Conference on Artificial Intelligence — 1× in this paper
• Interpretability — 1× in this paper · explained in 15 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• Transformer Architecture — 1× in this paper · explained in 2 episodes
• Transformer Models — 1× in this paper · explained in 2 episodes

Sources

• KAN: Kolmogorov-Arnold Networks
• ConvVitMamba: Efficient Multiscale Convolution, Transformer, and Mamba-Based Sequence modelling for Hyperspectral Image Classification

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