Multimedia, Indexing and Data Integration Group

The MIDI group works in the field of Big Data Management and Analytics, addressing topics that include integrating, mining, analyzing and querying large volumes of various types of data, going from structured and semi-structured data, to spatiotemporal data, text, image, video and 3D models. A particular accent is put on the design and use of Machine Learning techniques in contexts specific to data analysis and data processing problems, with a focus on the explainability and transparency of such algorithms. Applications include social media content and graph analytics, semantic web data integration and analysis, pattern detection in image, video and multimodal data, search engines for different types of data, knowledge extraction from data, data privacy, in application domains such as cultural heritage, security, opinion mining, health, etc.

Faculty

Research areas

• Indexing, analysis and research of visual content
• Learning for computer vision
• Massive Data Integration (Linked and Streaming data)
• Analysis and mining of social networks (graph structure and text)
• Mobility and spatio-temporal data analytics

Latest Publications

• [hal-03180441] Overlapping community detection using core label propagation algorithm and belonging functions
• [hal-03172873] Why-Not Questions & Explanations for Collaborative Filtering
• [hal-03107675] Learning Recurrent High-order Statistics for Skeleton-based Hand Gesture Recognition
• [hal-02558843] Multi-task Deep Learning for Real-Time 3D Human Pose Estimation and Action Recognition
• [tel-03095670] Solving Jigsaw Puzzles with Deep Learning for Heritage

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Voir aussi dans «Research»

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