用于高光谱图像场景分类的轻量级深度全局-局部知识蒸馏网络

Yingxu LIU, Chunyu PU, Diankun XU, Yichuan YANG, Hong HUANG
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引用次数: 0

摘要

Deep Global-Local Knowledge Distillation:LDGLKDï¼ç½ç "为æ¢ç´¢ç©º-Transformer(变压器):Vision Transformer(视觉变压器):ViT(智能变压器LDGLKD "VGG16 "系列在LDGLKD中,你会发现很多新功能,比如 "我可以做什么","我可以做什么","我可以做什么","我可以做什么","我可以做什么","我可以做什么","我可以做什么","我可以做什么","我可以做什么","我可以做什么","我可以做什么","我可以做什么","我可以做什么","我可以做什么","我可以做什么","我可以做什么"。SCHSRS-SC... 91.62%å97.96%的学生都在使用OHID-SCCACS。
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Lightweight deep global-local knowledge distillation network for hyperspectral image scene classification
é’ˆå¯¹ç›®æ ‡åœºæ™¯å¤æ‚çš„ç©ºé—´å¸ƒå±€å’Œé«˜å ‰è°±å½±åƒå›ºæœ‰çš„ç©º-è°±ä¿¡æ¯å†—ä½™ç­‰æŒ‘æˆ˜ï¼Œæå‡ºäº†ç«¯åˆ°ç«¯çš„è½»é‡åŒ–æ·±åº¦å ¨å±€-局部知识蒸馏(Lightweight Deep Global-Local Knowledge Distillation,LDGLKD)网络。为探索空-è°±ç‰¹å¾çš„å ¨å±€åºåˆ—å±žæ€§ï¼Œæ•™å¸ˆæ¨¡åž‹è§†è§‰Transformer(Vision Transformer,ViTï¼‰è¢«ç”¨æ¥æŒ‡å¯¼è½»é‡åŒ–å­¦ç”Ÿæ¨¡åž‹è¿›è¡Œé«˜å ‰è°±å½±åƒåœºæ™¯åˆ†ç±»ã€‚LDGLKD选择预训练的VGG16作为学生模型来提取局部细节信息,将ViT和VGG16é€šè¿‡çŸ¥è¯†è’¸é¦ååŒè®­ç»ƒåŽï¼Œæ•™å¸ˆæ¨¡åž‹å°†æ‰€å­¦ä¹ åˆ°çš„è¿œç¨‹ä¸Šä¸‹æ–‡å ³ç³»å‘å°è§„æ¨¡å­¦ç”Ÿæ¨¡åž‹è¿›è¡Œä¼ é€’ã€‚LDGLKDå¯é€šè¿‡çŸ¥è¯†è’¸é¦ç»“åˆä¸Šè¿°ä¸¤ç§æ¨¡åž‹çš„ä¼˜ç‚¹ï¼Œåœ¨æ¬§æ¯”ç‰¹é«˜å ‰è°±å½±åƒåœºæ™¯åˆ†ç±»æ•°æ®é›†OHID-SCåŠå ¬å¼€çš„é«˜å ‰è°±é¥æ„Ÿå›¾åƒæ•°æ®é›†HSRS-SC上的最佳分类精度分别达到91.62%和97.96%。实验结果表明:LDGLKDç½‘ç»œå ·æœ‰è‰¯å¥½çš„åˆ†ç±»æ€§èƒ½ã€‚æ ¹æ®æ¬§æ¯”ç‰¹ç æµ·ä¸€å·å«æ˜Ÿæä¾›çš„é¥æ„Ÿæ•°æ®æž„å»ºçš„OHID-SCå¯ä»¥åæ˜ è¯¦ç»†çš„åœ°è¡¨è¦†ç›–æƒ å†µï¼Œå¹¶ä¸ºé«˜å ‰è°±åœºæ™¯åˆ†ç±»ä»»åŠ¡æä¾›æ•°æ®æ”¯æ’‘ã€‚
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来源期刊
Guangxue Jingmi Gongcheng/Optics and Precision Engineering
Guangxue Jingmi Gongcheng/Optics and Precision Engineering Materials Science-Electronic, Optical and Magnetic Materials
CiteScore
2.40
自引率
0.00%
发文量
95
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