Multimodal Scene Understanding: Algorithms, Applications and Deep Learning
Ying Yang, Michael, Rosenhahn, Bodo, Murino, Vittorio
- 出版商: Academic Press
- 出版日期: 2019-07-17
- 售價: $4,980
- 貴賓價: 9.5 折 $4,731
- 語言: 英文
- 頁數: 422
- 裝訂: Quality Paper - also called trade paper
- ISBN: 0128173580
- ISBN-13: 9780128173589
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相關分類:
DeepLearning、Algorithms-data-structures
海外代購書籍(需單獨結帳)
相關主題
商品描述
Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and describes the role and approaches of multi-sensory data and multi-modal deep learning. The book is ideal for researchers from the fields of computer vision, remote sensing, robotics, and photogrammetry, thus helping foster interdisciplinary interaction and collaboration between these realms.
Researchers collecting and analyzing multi-sensory data collections - for example, KITTI benchmark (stereo+laser) - from different platforms, such as autonomous vehicles, surveillance cameras, UAVs, planes and satellites will find this book to be very useful.
- Contains state-of-the-art developments on multi-modal computing
- Shines a focus on algorithms and applications
- Presents novel deep learning topics on multi-sensor fusion and multi-modal deep learning
商品描述(中文翻譯)
《多模態場景理解:演算法、應用與深度學習》介紹了多模態計算的最新進展,專注於計算機視覺和攝影測量。本書提供了結合多種信息來源的最新演算法和應用,並描述了多感官數據和多模態深度學習的角色和方法。本書適合計算機視覺、遙感、機器人和攝影測量領域的研究人員閱讀,有助於促進這些領域之間的跨學科交流和合作。
從不同平台(例如自動駕駛車輛、監控攝像頭、無人機、飛機和衛星)收集和分析多感官數據集(例如KITTI基準測試(立體+激光))的研究人員將會發現本書非常有用。
本書特點如下:
- 包含多模態計算的最新發展
- 專注於演算法和應用
- 提出了關於多感官融合和多模態深度學習的新題目