English(EN)SpectralTrain: A Universal Framework for Hyperspectral Image Classification
新框架提升高光谱图像分类效率
作者PulseAugur 编辑部·[5 个来源]·
研究人员开发了几个用于高效高光谱图像分类的新框架，旨在降低计算成本并提高性能。SpectralTrain将课程学习与PCA集成以加快训练速度，而DE-CFFN使用因子分析和架构修改来实现数据效率。MixerSENet和SS-MixNet引入了带有混合器块和注意力机制的轻量级架构，以用更少的参数和更少的标记数据实现高精度。
AI
arXiv:2511.16084v3 Announce Type: replace-cross Abstract: Hyperspectral image (HSI) classification typically involves large-scale data and computationally intensive training, which limits the practical deployment of deep learning models in real-world remote sensing tasks. This st…
arXiv:2606.04710v1 Announce Type: new Abstract: This work presents a data-efficient variant of the Attention-Based Dual-Branch Complex Feature Fusion Network (CFFN) for hyperspectral image classification. The proposed model, termed DE-CFFN, retains the original two-stream structu…
This work presents a data-efficient variant of the Attention-Based Dual-Branch Complex Feature Fusion Network (CFFN) for hyperspectral image classification. The proposed model, termed DE-CFFN, retains the original two-stream structure: the Real-Valued Neural Network (RVNN) proces…
arXiv cs.CV
TIER_1English(EN)·Mohammed Q. Alkhatib, Swalpa Kumar Roy, Ali Jamali·
arXiv:2606.01700v1 Announce Type: new Abstract: In this paper, a novel framework, MixerSENet, is introduced for hyperspectral image (HSI) classification, designed to address the challenges of computational efficiency and limited labeled data. The proposed model processes hyperspe…
arXiv:2511.15692v2 Announce Type: replace Abstract: This paper introduces SS-MixNet, a lightweight and effective deep learning model for hyperspectral image (HSI) classification. The architecture integrates 3D convolutional layers for local spectral-spatial feature extraction wit…
