Zobrazeno 1 - 10
of 512
pro vyhledávání: '"Histace, A"'
Deep neural networks (DNNs) on Riemannian manifolds have garnered increasing interest in various applied areas. For instance, DNNs on spherical and hyperbolic manifolds have been designed to solve a wide range of computer vision and nature language p
Externí odkaz:
http://arxiv.org/abs/2405.19206
Deep anomaly detection (AD) aims to provide robust and efficient classifiers for one-class and unbalanced settings. However current AD models still struggle on edge-case normal samples and are often unable to keep high performance over different scal
Externí odkaz:
http://arxiv.org/abs/2211.09041
Autor:
Yael Tudela, Mireia Majó, Neil de la Fuente, Adrian Galdran, Adrian Krenzer, Frank Puppe, Amine Yamlahi, Thuy Nuong Tran, Bogdan J. Matuszewski, Kerr Fitzgerald, Cheng Bian, Junwen Pan, Shijle Liu, Gloria Fernández-Esparrach, Aymeric Histace, Jorge Bernal
Publikováno v:
Frontiers in Oncology, Vol 14 (2024)
IntroductionColorectal cancer (CRC) is one of the main causes of deaths worldwide. Early detection and diagnosis of its precursor lesion, the polyp, is key to reduce its mortality and to improve procedure efficiency. During the last two decades, seve
Externí odkaz:
https://doaj.org/article/059a0add1a84450499dc90757c953842
Autor:
Arnaud Cannet, Camille Simon-chane, Aymeric Histace, Mohammad Akhoundi, Olivier Romain, Marc Souchaud, Pierre Jacob, Darian Sereno, Philippe Bousses, Denis Sereno
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-6 (2024)
Abstract Several Diptera species are known to transmit pathogens of medical and veterinary interest. However, identifying these species using conventional methods can be time-consuming, labor-intensive, or expensive. A computer vision-based system th
Externí odkaz:
https://doaj.org/article/0331348904644a058bfb09156aa13d33
Publikováno v:
IEEE Access, Vol 12, Pp 38927-38943 (2024)
Polyp segmentation within colonoscopy video frames using deep learning models has the potential to automate colonoscopy screening procedures. This could help improve the early lesion detection rate and in vivo characterization of polyps which could d
Externí odkaz:
https://doaj.org/article/d67781d2e7da4b0e8fb3549584bb0a88
Anomaly detection is important in many real-life applications. Recently, self-supervised learning has greatly helped deep anomaly detection by recognizing several geometric transformations. However these methods lack finer features, usually highly de
Externí odkaz:
http://arxiv.org/abs/2111.12379
Autor:
Arnaud Cannet, Camille Simon-Chane, Aymeric Histace, Mohammad Akhoundi, Olivier Romain, Marc Souchaud, Pierre Jacob, Darian Sereno, Petr Volf, Vit Dvorak, Denis Sereno
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-9 (2023)
Abstract Sandflies (Diptera; Psychodidae) are medical and veterinary vectors that transmit diverse parasitic, viral, and bacterial pathogens. Their identification has always been challenging, particularly at the specific and sub-specific levels, beca
Externí odkaz:
https://doaj.org/article/7435674083784fc293a5e1379a458f86
Autor:
Arnaud Cannet, Camille Simon-Chane, Aymeric Histace, Mohammad Akhoundi, Olivier Romain, Marc Souchaud, Pierre Jacob, Darian Sereno, Louis-Clément Gouagna, Philippe Bousses, Françoise Mathieu-Daude, Denis Sereno
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Abstract Hematophagous insects belonging to the Aedes genus are proven vectors of viral and filarial pathogens of medical interest. Aedes albopictus is an increasingly important vector because of its rapid worldwide expansion. In the context of globa
Externí odkaz:
https://doaj.org/article/b52358abe9ec48e29847d0a03536e07f
Publikováno v:
L. J\'ez\'equel, N. -S. Vu, J. Beaudet and A. Histace, "Fine-grained anomaly detection via multi-task self-supervision," 2021 17th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 2021, pp. 1-8
Detecting anomalies using deep learning has become a major challenge over the last years, and is becoming increasingly promising in several fields. The introduction of self-supervised learning has greatly helped many methods including anomaly detecti
Externí odkaz:
http://arxiv.org/abs/2104.09993
Autor:
Arnaud Cannet, Camille Simon-Chane, Mohammad Akhoundi, Aymeric Histace, Olivier Romain, Marc Souchaud, Pierre Jacob, Darian Sereno, Karine Mouline, Christian Barnabe, Frédéric Lardeux, Philippe Boussès, Denis Sereno
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-13 (2023)
Abstract We present a new and innovative identification method based on deep learning of the wing interferential patterns carried by mosquitoes of the Anopheles genus to classify and assign 20 Anopheles species, including 13 malaria vectors. We provi
Externí odkaz:
https://doaj.org/article/6ec3a830d6494cde997f37ae21c762d4