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Several techniques utilizing deep learning have been created to detect anomalies, yet their effectiveness on real\u2010world data is often limited due to the insufficient incorporation of motion patterns. To address these problems and enhance the traditional functionality of anomaly detection systems for surveillance video data, we propose a weakly supervised graph neural\u2010network\u2010assisted video anomaly detection framework called AD\u2010Graph. To identify temporal information from a series of frames, we extract 3D visual and motion features and represent these in a language\u2010based knowledge graph format. Next, a robust clustering strategy is applied to group together meaningful neighbourhoods of the graph with similar vertices. Furthermore, spectral filters are applied to these graphs, and spectral graph theory is used to generate graph signals and detect anomalous events. Extensive experimental results over two challenging datasets, UCF\u2010Crime and ShanghaiTech, show improvements of 0.35% and 0.78% against a state\u2010of\u2010the\u2010art model.<\/jats:p>","DOI":"10.1155\/2023\/7868415","type":"journal-article","created":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T23:35:08Z","timestamp":1690846508000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["AD\u2010Graph: Weakly Supervised Anomaly Detection Graph Neural Network"],"prefix":"10.1155","volume":"2023","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5191-9023","authenticated-orcid":false,"given":"Waseem","family":"Ullah","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4861-8347","authenticated-orcid":false,"given":"Tanveer","family":"Hussain","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1243-9358","authenticated-orcid":false,"given":"Fath U","family":"Min Ullah","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5302-1150","authenticated-orcid":false,"given":"Khan","family":"Muhammad","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5655-8511","authenticated-orcid":false,"given":"Mahmoud","family":"Hassaballah","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8657-3800","authenticated-orcid":false,"given":"Joel J. 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