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Titlebook: Big Data; 11th CCF Conference, Enhong Chen,Yang Gao,Wanqi Yang Conference proceedings 2023 The Editor(s) (if applicable) and The Author(s),

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11#
發(fā)表于 2025-3-23 11:36:38 | 只看該作者
,Dataset Search over?Integrated Metadata from?China’s Public Data Open Platforms,ment and digital economy. These activities rely on an infrastructure software called public data open platform (PDOP) to provide enabling services. While China’s national PDOP has yet to be completed, one pathway is to integrate the existing hundreds of provincial-level and prefectural-level PDOPs.
12#
發(fā)表于 2025-3-23 16:53:36 | 只看該作者
13#
發(fā)表于 2025-3-23 18:10:10 | 只看該作者
14#
發(fā)表于 2025-3-24 00:36:34 | 只看該作者
OCWYOLO: A Road Depression Detection Method,oint cloud modeling and segmentation based methods, (3) based on machine/deep learning methods, and (2) (3) hybrid methods. This article proposes a road depression detection algorithm based on Yolov7, which utilizes the Yolov7 network model to make different improvements: to make the localization mo
15#
發(fā)表于 2025-3-24 04:51:05 | 只看該作者
,Explicit Exploring Geometric Modality for?Shape-Enhanced Single-View 3D Face Reconstruction,ed approaches learn the geometry parameters directly from the 2D image appearance, but the limited information makes it an ill-conditioned task and makes the model struggle to learn the inference evidences. In this work, we propose that the 2D face boundary image contains more semantic information i
16#
發(fā)表于 2025-3-24 06:58:06 | 只看該作者
17#
發(fā)表于 2025-3-24 11:05:31 | 只看該作者
18#
發(fā)表于 2025-3-24 16:59:56 | 只看該作者
,Twin Support Vector Regression with?Privileged Information,ctive performance of twin support vector regression by incorporating additional privileged information during the learning process. This TSVR+ introduces a twin-learning strategy that utilizes both original and privileged features to construct two non-parallel boundary functions. One for positive de
19#
發(fā)表于 2025-3-24 19:48:49 | 只看該作者
Detecting Social Robots Based on Multi-view Graph Transformer,ts has become a long-standing but unresolved problem. Traditional machine learning models or methods have gradually become ineffective with the evolution of social robots. In contrast, analyzing the social network structure where social robots are located has become a more effective method. However,
20#
發(fā)表于 2025-3-24 23:25:50 | 只看該作者
,Scheduling Containerized Workflow in?Multi-cluster Kubernetes,rkflows. This combination provides unprecedented speed, scalability, and efficiency in deploying and managing applications in distributed environments. However, when scheduling complex workflows across multi-cluster Kubernetes environments, existing workflow scheduling systems often fail to provide
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