Query-centric video summarization focuses on generating concise video summaries that are tailored to a user's specific query or interest, rather than providing a generic overview. Unlike generic video summarization, which selects key frames or segments based on overall importance, query-centric approaches align the summary with semantic relevance to the input query. Techniques often leverage natural language processing, feature fusion, and deep learning to match visual content with textual queries, ensuring the resulting summary is both informative and contextually relevant. This improves user satisfaction by providing personalized, query-driven insights from large volumes of video data.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Query-centric video summarization focuses on generating concise video summaries that are tailored to a user's specific query or interest, rather than providing a generic overview. Unlike generic video summarization, which selects key frames or segments based on overall importance, query-centric approaches align the summary with semantic relevance to the input query. Techniques often leverage natural language processing, feature fusion, and deep learning to match visual content with textual queries, ensuring the resulting summary is both informative and contextually relevant. This improves user satisfaction by providing personalized, query-driven insights from large volumes of video data. 148 pp. Englisch. Nº de ref. del artículo: 9786209037610
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Paperback. Condición: new. Paperback. Query-centric video summarization focuses on generating concise video summaries that are tailored to a user's specific query or interest, rather than providing a generic overview. Unlike generic video summarization, which selects key frames or segments based on overall importance, query-centric approaches align the summary with semantic relevance to the input query. Techniques often leverage natural language processing, feature fusion, and deep learning to match visual content with textual queries, ensuring the resulting summary is both informative and contextually relevant. This improves user satisfaction by providing personalized, query-driven insights from large volumes of video data. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9786209037610
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Taschenbuch. Condición: Neu. Query Centric Language accompanied Automatic Video Summarization | Personalized Video Summary Generation | Rakhi Akhare (u. a.) | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786209037610 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu Print on Demand. Nº de ref. del artículo: 134243411
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Query-centric video summarization focuses on generating concise video summaries that are tailored to a user's specific query or interest, rather than providing a generic overview. Unlike generic video summarization, which selects key frames or segments based on overall importance, query-centric approaches align the summary with semantic relevance to the input query. Techniques often leverage natural language processing, feature fusion, and deep learning to match visual content with textual queries, ensuring the resulting summary is both informative and contextually relevant. This improves user satisfaction by providing personalized, query-driven insights from large volumes of video data.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 148 pp. Englisch. Nº de ref. del artículo: 9786209037610
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Query-centric video summarization focuses on generating concise video summaries that are tailored to a user's specific query or interest, rather than providing a generic overview. Unlike generic video summarization, which selects key frames or segments based on overall importance, query-centric approaches align the summary with semantic relevance to the input query. Techniques often leverage natural language processing, feature fusion, and deep learning to match visual content with textual queries, ensuring the resulting summary is both informative and contextually relevant. This improves user satisfaction by providing personalized, query-driven insights from large volumes of video data. Nº de ref. del artículo: 9786209037610
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