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Titlebook: Computer Supported Cooperative Work and Social Computing; 18th CCF Conference, Yuqing Sun,Tun Lu,Bowen Du Conference proceedings 2024 The E

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樓主: CYNIC
21#
發(fā)表于 2025-3-25 06:37:56 | 只看該作者
Information Technology and Global Governanceorm constraint and sets the average flight distance of the weapon as the second optimization objective. In response to such problems, this paper proposes an improved multi-objective auction algorithm, which is based on the traditional auction algorithm and the non-dominated sorting strategy, improve
22#
發(fā)表于 2025-3-25 08:11:09 | 只看該作者
The Content Governance Dilemma,ual annotation has been used as a means to label images. However, manual annotation is laborious and time-consuming and can introduce additional noise. To address these issues, this paper investigates an automatic algorithm for improving a cat breed classification model based on meta loss correction
23#
發(fā)表于 2025-3-25 13:09:56 | 只看該作者
24#
發(fā)表于 2025-3-25 16:17:38 | 只看該作者
Annulla Linders,Marina Kalanderignment (GRA), and role transfer. Among these stages, GRA holds significant importance as a critical step in the process. In Social Sciences, trust between group members in collaboration tends to profoundly impact the final performance. However, existing GRA problems neglected the trust relationship
25#
發(fā)表于 2025-3-25 20:19:17 | 只看該作者
26#
發(fā)表于 2025-3-26 03:07:50 | 只看該作者
Annulla Linders,Marina Kalandeributions from researchers in solving LSOPs, the large search space and the numerous local optimal solutions of LSOPs are still two important challenges. In order to alleviate the above challenges, this paper proposes a dimension-based elite learning particle swarm optimizer (DELPSO). In DELPSO, indi
27#
發(fā)表于 2025-3-26 06:43:41 | 只看該作者
28#
發(fā)表于 2025-3-26 09:19:45 | 只看該作者
Johan Christensen,Cathrine Holst hand, simply using Chinese-English rich resources to expand the training data faces problems in disentangling of linguistic feature and speaker timbre feature. This paper proposes to build a cross-lingual feature disentangler and incorporate Time-Frequency Attention Adaptive Normalization (TFAAN) t
29#
發(fā)表于 2025-3-26 12:55:49 | 只看該作者
https://doi.org/10.1007/978-3-030-44105-0 actions. Most of the existing methods analyze video data without considering the spatial information of human joints. Although the classification of single-frame action has achieved remarkable results, there are challenges in over-segmentation under high precision. To address this challenge, we pro
30#
發(fā)表于 2025-3-26 19:45:58 | 只看該作者
In the Name of Silence and Destruction,In the course of our research on convolutional neural networks (CNNs), we have discovered a novel model aggregation method called CoME, which accelerates model training speed, enhances model precision, and exhibits good interpretability. Starting from the relationship between convolutions and planar
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