000 | 01660nam a22002297a 4500 | ||
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999 |
_c4510 _d4510 |
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005 | 20230120142918.0 | ||
008 | 230120b ||||| |||| 00| 0 eng d | ||
020 | _a9789811218835 | ||
082 |
_a006.31 _bCHE |
||
245 |
_aGeneralization with deep learning: _bfor improvement on sensing capability |
||
260 |
_bWorld Scientific Publishing Company Pvt. Ltd. _aNew Jersey _c2021 |
||
300 | _axii, 314 p. | ||
365 |
_aUSD _b108.00 |
||
520 | _aDeep Learning has achieved great success in many challenging research areas, such as image recognition and natural language processing. The key merit of deep learning is to automatically learn good feature representation from massive data conceptually. In this book, we will show that the deep learning technology can be a very good candidate for improving sensing capabilities. In this edited volume, we aim to narrow the gap between humans and machines by showcasing various deep learning applications in the area of sensing. The book will cover the fundamentals of deep learning techniques and their applications in real-world problems including activity sensing, remote sensing and medical sensing. It will demonstrate how different deep learning techniques help to improve the sensing capabilities and enable scientists and practitioners to make insightful observations and generate invaluable discoveries from different types of data. | ||
650 |
_aMachine learning _92343 |
||
650 |
_aRemote sensing--Data processing _911504 |
||
650 |
_aDiagnostic imaging--Data processing _911505 |
||
700 |
_aChen, Zhenghua _911506 |
||
700 |
_aWu, Min _911507 |
||
700 |
_aLi, Xiaoli _911508 |
||
942 |
_2ddc _cBK |