Random shuffling data for hyperspectral image classification with Siamese and Knowledge Distillation Network

• المؤلفون الرئيسيون: Yang, Zhen, Cao, Ying, Zhou, Xin, Liu, Junya, Zhang, Tao, Ji, Jinsheng
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2023
• الموضوعات: Engineering::Electrical and electronic engineering; Local Contextual Information; Random Shuffling Strategy
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/171662

Hyperspectral images (HSIs) are characterized by hundreds of spectral bands. The goal of HSI is to associate the pixel with a corresponding category label by analyzing subtle differences in the spectrum. Due to their excellent local context modeling capabilities, Convolutional Neural Network (CNN)-b...