Searched for: subject%3A%22self%255C-supervised%255C+learning%22
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Xu, Y. (author)
Micro air vehicles (MAVs) have shown significant potential in modern society. The development in robotics and automation is changing the roles of MAVs from remotely controlled machines requiring human pilots to autonomous and intelligent robots. There is an increasing number of autonomous MAVs involved in outdoor operations. In contrast, the...
doctoral thesis 2023
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Duan, Di (author), Yang, Huanqi (author), Lan, G. (author), Li, Tianxing (author), Jia, Xiaohua (author), Xu, Weitao (author)
This paper presents EMGSense, a low-effort self-supervised domain adaptation framework for sensing applications based on Electromyography (EMG). EMGSense addresses one of the fundamental challenges in EMG cross-user sensing—the significant performance degradation caused by time-varying biological heterogeneity—in a low-effort (data-efficient and...
conference paper 2023
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Liu, C. (author), Xu, Y. (author), van Kampen, E. (author), de Croon, G.C.H.E. (author)
In this paper, we propose an obstacle avoidance solution for a 34-gram quadcopter equipped with a monocular camera. The perception of obstacles is tackled by a lightweight convolutional neural network predicting a dense depth map from a captured grey-scale image. The depth network performs self-supervised learning and thus requires no ground...
journal article 2023