Zobrazeno 1 - 10
of 364
pro vyhledávání: '"Macq Benoît"'
Autor:
Benkedadra, Mohamed, Rimez, Dany, Godelaine, Tiffanie, Chidambaram, Natarajan, Khosroshahi, Hamed Razavi, Tellez, Horacio, Mancas, Matei, Macq, Benoit, Mahmoudi, Sidi Ahmed
Publikováno v:
2024 IEEE 7th International Conference on Multimedia Information Processing and Retrieval (MIPR) 2024 IEEE 7th International Conference on Multimedia Information Processing and Retrieval (MIPR) 10.1109/MIPR62202.2024
Computer vision tasks such as object detection and segmentation rely on the availability of extensive, accurately annotated datasets. In this work, We present CIA, a modular pipeline, for (1) generating synthetic images for dataset augmentation using
Externí odkaz:
http://arxiv.org/abs/2411.16128
Autor:
Dausort, Manon, Godelaine, Tiffanie, Zanella, Maxime, Khoury, Karim El, Salmon, Isabelle, Macq, Benoît
Cytology slides are essential tools in diagnosing and staging cancer, but their analysis is time-consuming and costly. Foundation models have shown great potential to assist in these tasks. In this paper, we explore how existing foundation models can
Externí odkaz:
http://arxiv.org/abs/2411.14975
Autor:
Halin, Anaïs, Piérard, Sébastien, Vandeghen, Renaud, Gérin, Benoît, Zanella, Maxime, Colot, Martin, Held, Jan, Cioppa, Anthony, Jean, Emmanuel, Bontempi, Gianluca, Mahmoudi, Saïd, Macq, Benoît, Van Droogenbroeck, Marc
Characterizing domains is essential for models analyzing dynamic environments, as it allows them to adapt to evolving conditions or to hand the task over to backup systems when facing conditions outside their operational domain. Existing solutions ty
Externí odkaz:
http://arxiv.org/abs/2411.14827
Autor:
Bary, Tim, Macq, Benoit
Transformer neural networks require a large amount of labeled data to train effectively. Such data is often scarce in electroencephalography, as annotations made by medical experts are costly. This is why self-supervised training, using unlabeled dat
Externí odkaz:
http://arxiv.org/abs/2410.07190
Autor:
Khoury, Karim El, Zanella, Maxime, Gérin, Benoît, Godelaine, Tiffanie, Macq, Benoît, Mahmoudi, Saïd, De Vleeschouwer, Christophe, Ayed, Ismail Ben
Vision-Language Models for remote sensing have shown promising uses thanks to their extensive pretraining. However, their conventional usage in zero-shot scene classification methods still involves dividing large images into patches and making indepe
Externí odkaz:
http://arxiv.org/abs/2409.00698
Autor:
Gérin, Benoît, Halin, Anaïs, Cioppa, Anthony, Henry, Maxim, Ghanem, Bernard, Macq, Benoît, De Vleeschouwer, Christophe, Van Droogenbroeck, Marc
In the era of the Internet of Things (IoT), objects connect through a dynamic network, empowered by technologies like 5G, enabling real-time data sharing. However, smart objects, notably autonomous vehicles, face challenges in critical local computat
Externí odkaz:
http://arxiv.org/abs/2404.17930
We present a scalable framework designed to craft efficient lightweight models for video object detection utilizing self-training and knowledge distillation techniques. We scrutinize methodologies for the ideal selection of training images from video
Externí odkaz:
http://arxiv.org/abs/2404.10411
Emergency response missions depend on the fast relay of visual information, a task to which unmanned aerial vehicles are well adapted. However, the effective use of unmanned aerial vehicles is often compromised by bandwidth limitations that impede fa
Externí odkaz:
http://arxiv.org/abs/2402.04673
Autor:
Piérard, Sébastien, Cioppa, Anthony, Halin, Anaïs, Vandeghen, Renaud, Zanella, Maxime, Macq, Benoît, Mahmoudi, Saïd, Van Droogenbroeck, Marc
Various tasks encountered in real-world surveillance can be addressed by determining posteriors (e.g. by Bayesian inference or machine learning), based on which critical decisions must be taken. However, the surveillance domain (acquisition device, o
Externí odkaz:
http://arxiv.org/abs/2211.10119
Purpose: To improve target coverage and reduce the dose in the surrounding organs-at-risks (OARs), we developed an image-guided treatment method based on a precomputed library of treatment plans controlled and delivered in real-time. Methods: A libra
Externí odkaz:
http://arxiv.org/abs/2211.00389