{"product_id":"synthetic-aperture-radar-sar-meets-deep-learning-hardcover","title":"Synthetic Aperture Radar (SAR) Meets Deep Learning - Hardcover","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eTianwen Zhang\u003c\/b\u003e (Guest Editor), \u003cb\u003eTianjiao Zeng\u003c\/b\u003e (Guest Editor), \u003cb\u003eXiaoling Zhang\u003c\/b\u003e (Guest Editor)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eThis reprint focuses on the application of the combination of synthetic aperture radars and depth learning technology. It aims to further promote the development of SAR image intelligent interpretation technology.\u003c\/p\u003e\u003cp\u003eA synthetic aperture radar (SAR) is an important active microwave imaging sensor, whose all-day and all-weather working capacity give it an important place in the remote sensing community. Since the United States launched the first SAR satellite, SAR has received much attention in the remote sensing community, e.g., in geological exploration, topographic mapping, disaster forecast, and traffic monitoring. It is valuable and meaningful, therefore, to study SAR-based remote sensing applications.\u003c\/p\u003e\u003cp\u003eIn recent years, deep learning represented by convolution neural networks has promoted significant progress in the computer vision community, e.g., in face recognition, the driverless field and Internet of things (IoT). Deep learning can enable computational models with multiple processing layers to learn data representations with multiple-level abstractions. This can greatly improve the performance of various applications.\u003c\/p\u003e\u003cp\u003eThis reprint provides a platform for researchers to handle the above significant challenges and present their innovative and cutting-edge research results when applying deep learning to SAR in various manuscript types, e.g., articles, letters, reviews and technical reports.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 386\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 1.19 x 9.61 x 6.69 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e February 01, 2023\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":47667360858333,"sku":"9783036563824","price":133.77,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0811\/9867\/8237\/files\/RIihroBY9n9783036563824.webp?v=1773921340","url":"https:\/\/handfulofbooks.com\/products\/synthetic-aperture-radar-sar-meets-deep-learning-hardcover","provider":"Handful of Books","version":"1.0","type":"link"}