AssociativeFormer: Integrating Sparse Memory Attention and Versatile Tokenization for Hyperspectral Image Classification

Developing hyperspectral image classification models has long been hindered by problems regarding spectral redundancy and complexity, as well as the limitations of previously proposed transformer methods. We present <italic>AssociativeFormer</italic>, an architecture designed to address hyperspectra...

תיאור מלא

מידע ביבליוגרפי

Principais autores:	Ayesha Shafique, Mohammad Siraj, Saad Sohail, Saif A. Alsaif, Benmao Cheng
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	IEEE 2026-01-01
סדרה:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
נושאים:	Associative memory hyperspectral image classification remote sensing sparse attention spatial-spectral tokenization transformer networks
גישה מקוונת:	https://ieeexplore.ieee.org/document/11481669/
תגים:	הוספת תג אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!