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Xinzhi Liu, Jun Yu, Toru Kurihara, Congzhong Wu, Zhao Niu and Shu Zhan
It seems difficult to recognize an object from its background with similar color using conventional segmentation methods. An efficient way is to utilize hyperspectral images that contain more wave bands and richer information than only RGB components. Pa...
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Nikolaos Makrakis, Prodromos N. Psarropoulos and Yiannis Tsompanakis
Large-scale lifelines in seismic-prone regions very frequently cross areas that are characterized by active tectonic faulting, as complete avoidance might be techno-economically unfeasible. The resulting Permanent Ground Displacements (PGDs) constitute a...
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Guilherme Perin, Lichao Wu and Stjepan Picek
The adoption of deep neural networks for profiling side-channel attacks opened new perspectives for leakage detection. Recent publications showed that cryptographic implementations featuring different countermeasures could be broken without feature selec...
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Youngki Park and Youhyun Shin
In this paper, we introduce an efficient approach to multi-label image classification that is particularly suited for scenarios requiring rapid adaptation to new classes with minimal training data. Unlike conventional methods that rely solely on neural n...
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Eike Jakubowitz, Thekla Feist, Alina Obermeier, Carina Gempfer, Christof Hurschler, Henning Windhagen and Max-Heinrich Laves
Human grasping is a relatively fast process and control signals for upper limb prosthetics cannot be generated and processed in a sufficiently timely manner. The aim of this study was to examine whether discriminating between different grasping movements...
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