المؤلفون: Danfeng Huang, Chunpei Lin, Fang Zhong, Hailin Li, Fan Yang

المصدر: Transinformação, Vol 36 (2024)

مصطلحات موضوعية: Overseas Chines, Co-occurrence relation, Literature analysis, Source of publication, Network Structure, Museums. Collectors and collecting, AM1-501, Bibliography. Library science. Information resources

الوصف: Abstract In the past ten years, new progress has been made in the study of Chinese overseas, which provides important scientific basis for the work of Chinese overseas and the formulation of relevant policies. Through data mining and analysis of overseas Chinese literature from 2008 to 2021, this work studied the co-occurrence relationships among keywords, authors, research institutions, publication sources of target articles, references and citations. The results suggest a few things. In terms of keyword analysis, there is a high probability that keywords coexist among overseas Chinese, Chinese society and Chinese history. In addition, the degree of cooperation between authors and research institutions in overseas research in China is not high. In terms of target journals, references and citations, resources such as Journal of Overseas Chinese Historical Studies, Overseas Chinese Publishing Company and People’s Publishing House are the main publications published by most overseas Chinese research institutions. In addition, academic articles cite fewer of the journal’s journals. Based on the above problems, this study puts forward relevant recommendations for decision-making, in order to further promote the exchange, sharing and development of China’s overseas research results.

وصف الملف: electronic resource

Relation: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-37862024000100501&tlng=en; https://doaj.org/toc/2318-0889

URL الوصول: https://doaj.org/article/e60f6a645d364d15a26e6d79c29684c5

المؤلفون: Gong, Jingyu, Ye, Zhou, Ma, Lizhuang^{Aff1, Aff3, IDs4109502102446_cor3}

المصدر: Computational Visual Media. 8(2):303-315

المؤلفون: Jingyu Gong, Zhou Ye, Lizhuang Ma

المصدر: Computational Visual Media, Vol 8, Iss 2, Pp 303-315 (2021)

مصطلحات موضوعية: 3D vision, point cloud, co-occurrence relation modeling, semantic segmentation, Electronic computers. Computer science, QA75.5-76.95

الوصف: Abstract A significant performance boost has been achieved in point cloud semantic segmentation by utilization of the encoder-decoder architecture and novel convolution operations for point clouds. However, co-occurrence relationships within a local region which can directly influence segmentation results are usually ignored by current works. In this paper, we propose a neighborhood co-occurrence matrix (NCM) to model local co-occurrence relationships in a point cloud. We generate target NCM and prediction NCM from semantic labels and a prediction map respectively. Then, Kullback-Leibler (KL) divergence is used to maximize the similarity between the target and prediction NCMs to learn the co-occurrence relationship. Moreover, for large scenes where the NCMs for a sampled point cloud and the whole scene differ greatly, we introduce a reverse form of KL divergence which can better handle the difference to supervise the prediction NCMs. We integrate our method into an existing backbone and conduct comprehensive experiments on three datasets: Semantic3D for outdoor space segmentation, and S3DIS and ScanNet v2 for indoor scene segmentation. Results indicate that our method can significantly improve upon the backbone and outperform many leading competitors.

وصف الملف: electronic resource

Relation: https://doaj.org/toc/2096-0433; https://doaj.org/toc/2096-0662

URL الوصول: https://doaj.org/article/f938fcfbe67b4a61a47ac975ba983adb

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