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• W3100011500 abstract "Hyperspectral image (HSI) classification has become a hot topic in the field of remote sensing. In general, the complex characteristics of hyperspectral data make the accurate classification of such data challenging for traditional machine learning methods. In addition, hyperspectral imaging often deals with an inherently nonlinear relation between the captured spectral information and the corresponding materials. In recent years, deep learning has been recognized as a powerful feature-extraction tool to effectively address nonlinear problems and widely used in a number of image processing tasks. Motivated by those successful applications, deep learning has also been introduced to classify HSIs and demonstrated good performance. This survey paper presents a systematic review of deep learning-based HSI classification literatures and compares several strategies for this topic. Specifically, we first summarize the main challenges of HSI classification which cannot be effectively overcome by traditional machine learning methods, and also introduce the advantages of deep learning to handle these problems. Then, we build a framework that divides the corresponding works into spectral-feature networks, spatial-feature networks, and spectral-spatial-feature networks to systematically review the recent achievements in deep learning-based HSI classification. In addition, considering the fact that available training samples in the remote sensing field are usually very limited and training deep networks require a large number of samples, we include some strategies to improve classification performance, which can provide some guidelines for future studies on this topic. Finally, several representative deep learning-based classification methods are conducted on real HSIs in our experiments." @default.
• W3100011500 created "2020-11-23" @default.
• W3100011500 creator A5002687387 @default.
• W3100011500 creator A5019995639 @default.
• W3100011500 creator A5027034650 @default.
• W3100011500 creator A5065061505 @default.
• W3100011500 creator A5067097659 @default.
• W3100011500 creator A5074919292 @default.
• W3100011500 date "2019-09-01" @default.
• W3100011500 modified "2023-10-16" @default.
• W3100011500 title "Deep Learning for Hyperspectral Image Classification: An Overview" @default.
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• W3100011500 cites W1939429412 @default.
• W3100011500 cites W1950365613 @default.
• W3100011500 cites W1966580635 @default.
• W3100011500 cites W1972085588 @default.
• W3100011500 cites W1990895816 @default.
• W3100011500 cites W1998030734 @default.
• W3100011500 cites W2004104348 @default.
• W3100011500 cites W2016589492 @default.
• W3100011500 cites W2029316659 @default.
• W3100011500 cites W2045095960 @default.
• W3100011500 cites W2052160904 @default.
• W3100011500 cites W2058795991 @default.
• W3100011500 cites W2059089906 @default.
• W3100011500 cites W2064675550 @default.
• W3100011500 cites W2090424610 @default.
• W3100011500 cites W2097117768 @default.
• W3100011500 cites W2097915756 @default.
• W3100011500 cites W2098676252 @default.
• W3100011500 cites W2102605133 @default.
• W3100011500 cites W2103094532 @default.
• W3100011500 cites W2107878631 @default.
• W3100011500 cites W2113464037 @default.
• W3100011500 cites W2114819256 @default.
• W3100011500 cites W2136251662 @default.
• W3100011500 cites W2140340527 @default.
• W3100011500 cites W2144151128 @default.
• W3100011500 cites W2153635508 @default.
• W3100011500 cites W2158400785 @default.
• W3100011500 cites W2162698522 @default.
• W3100011500 cites W2164330327 @default.
• W3100011500 cites W2166923144 @default.
• W3100011500 cites W2179290474 @default.
• W3100011500 cites W2194775991 @default.
• W3100011500 cites W2248723555 @default.
• W3100011500 cites W2257669061 @default.
• W3100011500 cites W2276858186 @default.
• W3100011500 cites W2289977264 @default.
• W3100011500 cites W2314785379 @default.
• W3100011500 cites W2345128667 @default.
• W3100011500 cites W2412588858 @default.
• W3100011500 cites W248389711 @default.
• W3100011500 cites W2500751094 @default.
• W3100011500 cites W2518831014 @default.
• W3100011500 cites W2518897583 @default.
• W3100011500 cites W2527650001 @default.
• W3100011500 cites W2547846938 @default.
• W3100011500 cites W2548791488 @default.
• W3100011500 cites W2558391528 @default.
• W3100011500 cites W2560523472 @default.
• W3100011500 cites W2565258258 @default.
• W3100011500 cites W2572303978 @default.
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• W3100011500 cites W2587790406 @default.
• W3100011500 cites W2592224809 @default.
• W3100011500 cites W2595902385 @default.
• W3100011500 cites W2600746131 @default.
• W3100011500 cites W2603422184 @default.
• W3100011500 cites W2603834682 @default.
• W3100011500 cites W2611655888 @default.
• W3100011500 cites W2613575128 @default.
• W3100011500 cites W2614326984 @default.
• W3100011500 cites W2623518586 @default.
• W3100011500 cites W2625436554 @default.
• W3100011500 cites W2732412926 @default.
• W3100011500 cites W2737996023 @default.
• W3100011500 cites W2757208835 @default.
• W3100011500 cites W2764276316 @default.
• W3100011500 cites W2765739551 @default.
• W3100011500 cites W2765923665 @default.
• W3100011500 cites W2766947113 @default.
• W3100011500 cites W2767651786 @default.
• W3100011500 cites W2767805377 @default.
• W3100011500 cites W2768211636 @default.
• W3100011500 cites W2768309288 @default.
• W3100011500 cites W2768537477 @default.
• W3100011500 cites W2768975974 @default.
• W3100011500 cites W2772452219 @default.
• W3100011500 cites W2773213684 @default.
• W3100011500 cites W2777427437 @default.
• W3100011500 cites W2779530678 @default.
• W3100011500 cites W2782517596 @default.
• W3100011500 cites W2782522152 @default.
• W3100011500 cites W2784118841 @default.
• W3100011500 cites W2789643644 @default.
• W3100011500 cites W2791006446 @default.

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