15 research outputs found

    IRIM at TRECVID2009: High Level Feature Extraction

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    International audienceThe IRIM group is a consortium of French teams working on Multimedia Indexing and Retrieval. This paper describes our participation to the TRECVID 2009 High Level Features detection task. We evaluated a large number of different descriptors (on TRECVID 2008 data) and tried different fusion strategies, in particular hierarchical fusion and genetic fusion. The best IRIM run has a Mean Inferred Average Precision of 0.1220, which is significantly above TRECVID 2009 HLF detection task median performance. We found that fusion of the classification scores from different classifier types improves the performance and that even with a quite low individual performance, audio descriptors can help

    Envenimation par piqûres de raies à Djibouti (prise en charge aux urgences et intérêt de l'anesthésie locorégionale)

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    La raie est responsable d'iune envenimation marine peu connue de nos régions mais constitue néanmoins un problème épidémiologique sous-estimé dans les zones intertropicales. Tapie dans les eaux peu profondes, l'annimal donne un violent coup de sa queue pour se défendre. Celle-ci armée d'un aiguillon venimeux, inflige le plus souvent une blessure au niveau des pieds, parfois pénétrante, et dont le venin est responsable d'une douleur intense persistante plusieurs heures. Essentiellement responsable d'une atteinte locorégionale, la morbidité est non négligeable du fait d'un recours à des traitements traditionnels, à une évolution spontanée vers l'infection et la nécrose cutanée, et à l'absence de prise en charge codifiée. L'équipe du GMC Bouffard à Djibouti, a réalisé une étude prospective, incluant 21 patients, pour évaluer un protocole de prise en charge en urgence de cette envenimation, incluant notamment une anesthésie locorégionale (ALR) pour le traitement de la douleur. Le recueil de l'évaluation de la douleur des patients à différents moments de la prise en charge confirme une douleur initiale anormalement intense (EVA à 7,47). Elle n'est pas soulagée par une titration de morphine qui ne permet une diminution de l'EVA que de 1,33 points. Cette étude préliminaire montre que l'ALR est la technique de choix dans cette indication devant son efficacité et sa rapidité d'action apportant une diminution de l'EVA 3,47 points en moins de quinze minutes. Une prise en charge chirurgicale peut s'avérer nécessaire dans les suites imédiates pour un débridement en profitant des effets de l'anesthésie, ou à distance dans le cadre d'une chirurgie réparatrice en cas de troubles trophiques ou d'évolution défavorable. Des précisions restent à apporter sur les indications chirurgicales et l'antibiothérapie probabiliste pour améliorer ce protocole pluridisciplinaire faisant intervenir urgentiste, anesthésiste et chirurgien.BORDEAUX2-BU Santé (330632101) / SudocPARIS-Bib. Serv.Santé Armées (751055204) / SudocSudocFranceF

    A Hybrid System for Defect Detection on Rail Lines through the Fusion of Object and Context Information

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    Defect detection on rail lines is essential for ensuring safe and efficient transportation. Current image analysis methods with deep neural networks (DNNs) for defect detection often focus on the defects themselves while ignoring the related context. In this work, we propose a fusion model that combines both a targeted defect search and a context analysis, which is seen as a multimodal fusion task. Our model performs rule-based decision-level fusion, merging the confidence scores of multiple individual models to classify rail-line defects. We call the model “hybrid” in the sense that it is composed of supervised learning components and rule-based fusion. We first propose an improvement to existing vision-based defect detection methods by incorporating a convolutional block attention module (CBAM) in the you only look once (YOLO) versions 5 (YOLOv5) and 8 (YOLOv8) architectures for the detection of defects and contextual image elements. This attention module is applied at different detection scales. The domain-knowledge rules are applied to fuse the detection results. Our method demonstrates improvements over baseline models in vision-based defect detection. The model is open for the integration of modalities other than an image, e.g., sound and accelerometer data

    Clinical Survey of Dengue Virus Circulation in the Republic of Djibouti between 2011 and 2014 Identifies Serotype 3 Epidemic and Recommends Clinical Diagnosis Guidelines for Resource Limited Settings.

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    Dengue virus is endemic globally, throughout tropical and sub-tropical regions. While the number of epidemics due to the four DENV serotypes is pronounced in East Africa, the total number of cases reported in Africa (16 million infections) remained at low levels compared to Asia (70 million infections). The French Armed forces Health Service provides epidemiological surveillance support in the Republic of Djibouti through the Bouffard Military hospital. Between 2011 and 2014, clinical and biological data of suspected dengue syndromes were collected at the Bouffard Military hospital and analyzed to improve Dengue clinical diagnosis and evaluate its circulation in East Africa. Examining samples from patients that presented one or more Dengue-like symptoms the study evidenced 128 Dengue cases among 354 suspected cases (36.2% of the non-malarial Dengue-like syndromes). It also demonstrated the circulation of serotypes 1 and 2 and reports the first epidemic of serotype 3 infections in Djibouti which was found in all of the hospitalized patients in this study. Based on these results we have determined that screening for Malaria and the presence of the arthralgia, gastro-intestinal symptoms and lymphopenia < 1,000cell/ mm3 allows for negative predictive value and specificity of diagnosis in isolated areas superior to 80% up to day 6. This study also provides evidence for an epidemic of Dengue virus serotype 3 previously not detected in Djibouti
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