{"id":26383,"date":"2025-01-09T10:20:40","date_gmt":"2025-01-09T09:20:40","guid":{"rendered":"https:\/\/lium.univ-lemans.fr\/?p=26383"},"modified":"2025-01-09T10:56:49","modified_gmt":"2025-01-09T09:56:49","slug":"information-extraction-and-analysis-from-news-videos","status":"publish","type":"post","link":"https:\/\/lium.univ-lemans.fr\/en\/information-extraction-and-analysis-from-news-videos\/","title":{"rendered":"Information Extraction and Analysis from News videos"},"content":{"rendered":"

Seminar from Sadok Mansouri, ATER at LIUM<\/h2>\n

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Date:<\/strong> 13\/01\/2025
\nTime:<\/strong> 10h00
\nPlace:<\/strong> IC2, Boardroom
\nSpeaker: <\/strong> Sadok Mansouri<\/a><\/a>
\n 
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Information Extraction and Analysis from News videos<\/strong><\/p>\n

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Information extraction from videos is an important research topic in content-based video indexing and retrieval. Indeed, the visual text present in news videos typically provides rich semantic information, such as person identities, location names, and event types, which serve as a high-level index. However, variations in text due to differences in size, style, orientation, and alignment, as well as the linguistic complexity of same text, particularly in Arabic language , make the problem of automatic information extraction extremely challenging.<\/p>\n

In this talk, I will introduce our implementation solution called SISAVIN (Semantic Indexing System for Arabic News Videos), which includes four subtasks: text detection and recognition, text classification, entity recognition, and event extraction. The SISAVIN framework is based on recent methods in computer vision and natural language processing (NLP).<\/p><\/div><\/div><\/div><\/div>

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 <\/div><\/div><\/div>","protected":false},"excerpt":{"rendered":"

Seminar from Sadok Mansouri, ATER at LIUM   Date: 13\/01\/2025 Time: 10h00 Place: IC2, Boardroom Speaker: Sadok Mansouri     Information Extraction and Analysis from News videos   Information extraction from videos is an important research topic in content-based video indexing and retrieval. Indeed, the visual text present in news videos typically provides rich semantic […]<\/p>\n

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