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In this work, we propose the Depth and Width Changeable Deep Kernel Learning\u2010based hyperspectral sensing data analysis algorithm. Compared with the traditional kernel learning\u2010based hyperspectral data classification, the proposed method has its advantages on the hyperspectral data classification. With the deep kernel learning, the feature is mapped through many times mapping and has the more discriminative ability. So, the deep kernel learning has the better performance compared with the multiple kernels learning. And it has the ability to adjust the network architecture for hyperspectral data space, with the optimization equation of the span bound. The experiments are implemented to testified the feasibility and performance of the algorithms on the hyperspectral data analysis, with the classification accuracy of hyperspectral data. The comprehensive analysis of the experiments shows that the proposed algorithm is feasible to hyperspectral sensor data analysis and its promising classification method in many areas data analysis.<\/jats:p>","DOI":"10.1155\/2021\/8842396","type":"journal-article","created":{"date-parts":[[2021,2,22]],"date-time":"2021-02-22T18:50:07Z","timestamp":1614019807000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Depth and Width Changeable Network\u2010Based Deep Kernel Learning\u2010Based Hyperspectral Sensor Data Analysis"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4099-2625","authenticated-orcid":false,"given":"Jing","family":"Liu","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7605-4860","authenticated-orcid":false,"given":"Tingting","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7109-4222","authenticated-orcid":false,"given":"Yulong","family":"Qiao","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2021,2,22]]},"reference":[{"key":"e_1_2_8_1_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2788044"},{"key":"e_1_2_8_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2015.2496253"},{"key":"e_1_2_8_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2666038"},{"key":"e_1_2_8_4_2","doi-asserted-by":"crossref","unstructured":"WangC. 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