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Derek T. Anderson
Researcher at University of Missouri
Publications - 200
Citations - 3805
Derek T. Anderson is an academic researcher from University of Missouri. The author has contributed to research in topics: Fuzzy logic & Choquet integral. The author has an hindex of 26, co-authored 186 publications receiving 3274 citations. Previous affiliations of Derek T. Anderson include University of Arizona & National Institutes of Health.
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Journal ArticleDOI
Comprehensive survey of deep learning in remote sensing: theories, tools, and challenges for the community
TL;DR: In this article, the authors provide a comprehensive survey of state-of-the-art remote sensing deep learning research for remote sensing applications, focusing on theories, tools, and challenges for the remote sensing community.
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Linguistic summarization of video for fall detection using voxel person and fuzzy logic
TL;DR: A method for recognizing human activity from linguistic summarizations of temporal fuzzy inference curves representing the states of a three-dimensional object called voxel person and a two level model for fall detection is presented.
Proceedings ArticleDOI
A system for change detection and human recognition in voxel space using the Microsoft Kinect sensor
TL;DR: Preliminary results indicate that the Kinect sensor does indeed work in a wider range of operating conditions and it can produce activity descriptions that match that of a human.
Journal ArticleDOI
A Comprehensive Survey of Deep Learning in Remote Sensing: Theories, Tools and Challenges for the Community
TL;DR: This work focuses on theories, tools, and challenges for the RS community, and focuses on unsolved challenges and opportunities as they relate to inadequate data sets, big data, and human-understandable solutions for modeling physical phenomena.
Proceedings ArticleDOI
Recognizing falls from silhouettes.
TL;DR: Preliminary results are presented that demonstrate the usefulness of the segmentation approach for distinguishing between a few common activities, specifically with fall detection in mind.