From raw signals to human skills level in physical human-robot collaboration for advanced-manufacturing applications

Autor: Amel Bouzeghoub, Katleen Blanchet, Patrick Hède, Olivier Lebec, Selma Kchir

Publikováno v: Neural Information Processing: 26th international conference, ICONIP 2019, Sydney, NSW, Australia, December 12–15, 2019, proceedings, part II
ICONIP 2019: 26th International Conference on Neural Information Processing
ICONIP 2019: 26th International Conference on Neural Information Processing, Dec 2019, Sydney, Australia. pp.554-565, ⟨10.1007/978-3-030-36711-4_47⟩
Neural Information Processing ISBN: 9783030367107
ICONIP (2)

International audience; Providing individualized assistance to a human when she/he is physically interacting with a robot is a challenge that necessarily entails user profiling. The identification of the human profile in advanced-manufacturing is onl

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f8085a5c98ab29904c965817f6d285ec
https://hal.science/hal-02450428

Automatic cleaning and segmentation of web images based on colors to build learning databases

Autor: Pierre-Alain Moëllic, Isabelle Bloch, Patrick Hède, Christophe Millet

Publikováno v: Image and Vision Computing. 28:317-328

This article proposes a method to segment Internet images, that is, a group of images corresponding to a specific object (the query) containing a significant amount of irrelevant images. The segmentation algorithm we propose is a combination of two d

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f8ea1e893a246a0212b25a10b4ecb0a8
https://doi.org/10.1016/j.imavis.2009.06.005

Evaluating Content Based Image Retrieval Techniques With The One Million Images Clic Test Bed

Autor: Pierre-Alain Moëllic, Patrick Hède, Gr egory Grefenstette, Christophe Millet

Pattern recognition and image recognition methods are commonly developed and tested using testbeds, which contain known responses to a query set. Until now, testbeds available for image analysis and content-based image retrieval (CBIR) have been scar

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::35bac801ecc763a762e3640b06084f66

Clustering and semantically filtering web images to create a large-scale image ontology

Autor: Patrick Hède, G Grefenstette, B Mathieu, P-A Moellic, Christophe Millet, Svitlana Zinger

Publikováno v: Proceedings of SPIE 18th Annual Symposium Electronic Imaging, Internet Imaging VII, 18 January 2006, San Jose, California, 89-97
STARTPAGE=89;ENDPAGE=97;TITLE=Proceedings of SPIE 18th Annual Symposium Electronic Imaging, Internet Imaging VII, 18 January 2006, San Jose, California

In our effort to contribute to the closing of the "semantic gap" between images and their semantic description, we are building a large-scale ontology of images of objects. This visual catalog will contain a large number of images of objects, structu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fa3e0b38c84f1a2a8c1aeb7e2522a8dc
https://research.tue.nl/nl/publications/9956e58b-af5e-4d25-b11d-cb62cc5749fc

Cross-Media Feedback Strategies: Merging Text and Image Information to Improve Image Retrieval

Autor: Patrick Hède, Christian Fluhr, Romaric Besançon, Pierre-Alain Moëllic

Publikováno v: Multilingual Information Access for Text, Speech and Images ISBN: 9783540274209
CLEF

The CEA-LIST/LIC2M develops both cross-language information retrieval systems and content-based image retrieval systems. The ad hoc and medical tasks of the ImageCLEF campaign offered us the opportunity to perform some experiments on merging the resu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::517d8204181ed149053b755fdce603f9
https://doi.org/10.1007/11519645_69