"Deep 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 human and machine by showcasing various deep learning applications in thearea 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"--
Deep 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 features from massive data conceptually. This technology can be a good candidate for human activity recognition. However, many challenging research problems in terms of accuracy, device heterogeneous, environment changes, etc. remain unsolved.
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