Hyperspectral Image: Research and Applications

Dear Colleagues,

The advances in hyperspectral imaging have significantly enhanced our capacity to collect intricate data pertaining to the Earth's surface. Nonetheless, effectively harnessing this wealth of spectral information remains a formidable task. Deep learning has emerged as a promising avenue, fundamentally transforming the classification of hyperspectral images by autonomously discerning complex spectral–spatial patterns. We invite contributions that push the boundaries of current knowledge in this dynamic domain, aiming to unlock fresh perspectives for more precise and impactful applications.

This Special Issue seeks to delve into the latest breakthroughs in leveraging deep learning methodologies for hyperspectral image research and applications. Researchers are urged to submit original research articles, reviews, or surveys. Submissions must uphold rigorous scientific standards, underscore the significance of their findings, and provide transparent experimental validation. We embrace submissions that tackle both theoretical advancements and practical applications.

Prof. Dr. Hongmin Gao
Dr. Mingxiang Yang
Guest Editors

Manuscript Submission Information

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