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Titlebook: Handbuch Mitarbeiterführung; Wirtschaftspsycholog J?rg Felfe,Rolf van Dick Book 20161st edition Springer-Verlag Berlin Heidelberg 2016 Führ

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31#
發(fā)表于 2025-3-27 00:16:55 | 只看該作者
Uwe Peter Kanningdifferent nature from numerical data. Here our focus is on the partition paradigm of algorithms. One existing approach is to transform categorical data into binary data and then use k-means. However it’s computationally inefficient. Another approach is k-modes, which extends k-means by replacing mea
32#
發(fā)表于 2025-3-27 04:41:36 | 只看該作者
Stefan L. D?rr,Marion Schmidt-Huber,Franz X. Inderst,Günter W. Maiered technologies for pipeline inspection. However, CCTV is only in charge of reflecting the pipeline‘s status with videos and images. Identifying and evaluating pipeline defects still require professional knowledge and the participation of experienced practitioners. Therefore, intelligent approaches
33#
發(fā)表于 2025-3-27 05:30:48 | 只看該作者
34#
發(fā)表于 2025-3-27 10:20:57 | 只看該作者
35#
發(fā)表于 2025-3-27 16:52:21 | 只看該作者
36#
發(fā)表于 2025-3-27 18:12:05 | 只看該作者
Gerit Saupe,Sabine Korek not be suitable for the detecting image and the transform matrix fails to combine the low-level features of the image. In this paper, we propose a novel salient object detection model that combines sparse and low-rank matrix recovery (SLRR) with the adaptive background template. Our SLRR model usin
37#
發(fā)表于 2025-3-28 00:09:18 | 只看該作者
38#
發(fā)表于 2025-3-28 04:50:56 | 只看該作者
39#
發(fā)表于 2025-3-28 08:52:19 | 只看該作者
Gwen Elprana,Alina Hernandez,Leena Pundtuence of temporal features of social network on the search for similarity group. In this paper, we model the social network through the temporal graph and define the similar group in the temporal social network. Then, the T-VF2 algorithm is designed to search the similarity group through the tempora
40#
發(fā)表于 2025-3-28 13:55:57 | 只看該作者
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