12 research outputs found

    Deformable Part-based Fully Convolutional Network for Object Detection

    Full text link
    Existing region-based object detectors are limited to regions with fixed box geometry to represent objects, even if those are highly non-rectangular. In this paper we introduce DP-FCN, a deep model for object detection which explicitly adapts to shapes of objects with deformable parts. Without additional annotations, it learns to focus on discriminative elements and to align them, and simultaneously brings more invariance for classification and geometric information to refine localization. DP-FCN is composed of three main modules: a Fully Convolutional Network to efficiently maintain spatial resolution, a deformable part-based RoI pooling layer to optimize positions of parts and build invariance, and a deformation-aware localization module explicitly exploiting displacements of parts to improve accuracy of bounding box regression. We experimentally validate our model and show significant gains. DP-FCN achieves state-of-the-art performances of 83.1% and 80.9% on PASCAL VOC 2007 and 2012 with VOC data only.Comment: Accepted to BMVC 2017 (oral

    LOW RESOLUTION CONVOLUTIONAL NEURAL NETWORK FOR AUTOMATIC TARGET RECOGNITION

    Get PDF
    International audienceIn this work, we present an extended study of image representations for automatic target recognition (ATR). More specifically , we tackle the issue of the image resolution influence on the classification performances, an understudied yet major parameter in image classification. Besides, we propose a parallel between low-resolution image recognition and image classification in a fine-grained context. Indeed, in these two particular cases, the main difficulty is to discriminate small details on very similar objects. In this paper, we evaluate Fisher Vectors and deep representations on two significant publicly available fine-grained oriented datasets with respect to the input image resolution. We also introduce LR-CNN, a deep structure designed for classification of low-resolution images with strong semantic content. This net provides rich compact features and outperforms both pre-trained deep features and Fisher Vectors. We also present visual results of our LR-CNN on Thales near-infrared images

    Classifying low-resolution images by integrating privileged information in deep CNNs

    No full text
    International audienceAs introduced by [1], the privileged information is a complementary datum related to a training example that is unavailable for the test examples. In this paper, we consider the problem of recognizing low-resolution images (targeted task), while leveraging their high-resolution version as privileged information. In this context, we propose a novel framework for integrating privileged information in the learning phase of a deep neural network. We present a natural multi-class formulation of the addressed problem, while providing an end-to-end training framework of the internal deep representations. Based on a detailed analysis of the state-of-the-art approaches, we propose a novel loss function, combining two different ways of computing indicators of an example’s difficulty, based on its privileged information. We experimentally validate our approach in various contexts, proving the interest of our model for different tasks such as fine-grained image classification or image recognition from a dataset containing annotation noise

    End-to-End Learning of Latent Deformable Part-Based Representations for Object Detection

    No full text
    International audienc

    Catchment virtual observatory for sharing flow and transport modelsoutputs: using residence time distribution to compare contrastingcatchments

    No full text
    International audienceThe distribution of groundwater residence time in a catchment provides synoptic information about catchmentfunctioning (e.g. nutrient retention and removal, hydrograph flashiness). In contrast with interpreted modelresults, which are often not directly comparable between studies, residence time distribution is a general outputthat could be used to compare catchment behaviors and test hypotheses about landscape controls on catchmentfunctioning. In this goal, we created a virtual observatory platform called Catchment Virtual Observatory forSharing Flow and Transport Model Outputs (COnSOrT). The main goal of COnSOrT is to collect outputs fromcalibrated groundwater models from a wide range of environments. By comparing a wide variety of catch-ments from different climatic, topographic and hydrogeological contexts, we expect to enhance understandingof catchment connectivity, resilience to anthropogenic disturbance, and overall functioning. The web-basedobservatory will also provide software tools to analyze model outputs. The observatory will enable modelersto test their models in a wide range of catchment environments to evaluate the generality of their findings androbustness of their post-processing methods. Researchers with calibrated numerical models can benefit fromobservatory by using the post-processing methods to implement a new approach to analyzing their data. Fieldscientists interested in contributing data could invite modelers associated with the observatory to test their modelsagainst observed catchment behavior. COnSOrT will allow meta-analyses with community contributions to gener-ate new understanding and identify promising pathways forward to moving beyond single catchment ecohydrology

    Avis de l'Anses relatif à la présence de parasites Toxocara spp. dans les viandes de sanglier sauvage

    No full text
    Citation suggĂ©rĂ©e : Anses. (2023). Avis relatif Ă  la prĂ©sence de parasites Toxocara spp. dans les viandes de sanglier sauvage (saisine 2023-SA-0055). Maisons-Alfort : Anses, 20 p.Des analyses sur les carcasses de sangliers sauvages inspectĂ©es dans les Ă©tablissements français de traitement de gibiers sauvages ont rĂ©vĂ©lĂ© depuis deux ans la prĂ©sence rĂ©guliĂšre de larves de Toxocara spp. Ce constat a conduit les services vĂ©tĂ©rinaires d'inspection Ă  saisir ces carcasses, conformĂ©ment Ă  l'article 45 du rĂšglement d'exĂ©cution (UE) n°2019/627 de la Commission du 15 mars 2019 qui prĂ©voit que les viandes prĂ©sentant une infestation parasitaire sont dĂ©clarĂ©es impropres Ă  la consommation humaine. La problĂ©matique pour le gestionnaire est double. Le premier enjeu est liĂ© au risque de toxocarose pour les consommateurs de viandes de sanglier et des recommandations relatives Ă  la conservation et la cuisson des viandes Ă  adresser aux chasseurs. Le second enjeu est relatif Ă  la gestion des lots de sangliers dĂ©tectĂ©s positifs.Les demandes instruites dans le cadre de cette expertise sont les suivantes :Demande 1 : Établir un profil de risque pour Toxocara spp. dans les viandes de sanglier sauvage.Demande 2 : Évaluer l’efficacitĂ© de traitements assainissants de la carcasse sur la viabilitĂ© duparasite Toxocara spp., plus particuliĂšrement la congĂ©lation et la cuisson, dans le cas oĂč cestraitements sont rĂ©alisĂ©s, soit par les Ă©tablissements du secteur alimentaire, soit directementpar les consommateurs

    Avis de l'Anses relatif à la présence de parasites Toxocara spp. dans les viandes de sanglier sauvage

    No full text
    Citation suggĂ©rĂ©e : Anses. (2023). Avis relatif Ă  la prĂ©sence de parasites Toxocara spp. dans les viandes de sanglier sauvage (saisine 2023-SA-0055). Maisons-Alfort : Anses, 20 p.Des analyses sur les carcasses de sangliers sauvages inspectĂ©es dans les Ă©tablissements français de traitement de gibiers sauvages ont rĂ©vĂ©lĂ© depuis deux ans la prĂ©sence rĂ©guliĂšre de larves de Toxocara spp. Ce constat a conduit les services vĂ©tĂ©rinaires d'inspection Ă  saisir ces carcasses, conformĂ©ment Ă  l'article 45 du rĂšglement d'exĂ©cution (UE) n°2019/627 de la Commission du 15 mars 2019 qui prĂ©voit que les viandes prĂ©sentant une infestation parasitaire sont dĂ©clarĂ©es impropres Ă  la consommation humaine. La problĂ©matique pour le gestionnaire est double. Le premier enjeu est liĂ© au risque de toxocarose pour les consommateurs de viandes de sanglier et des recommandations relatives Ă  la conservation et la cuisson des viandes Ă  adresser aux chasseurs. Le second enjeu est relatif Ă  la gestion des lots de sangliers dĂ©tectĂ©s positifs.Les demandes instruites dans le cadre de cette expertise sont les suivantes :Demande 1 : Établir un profil de risque pour Toxocara spp. dans les viandes de sanglier sauvage.Demande 2 : Évaluer l’efficacitĂ© de traitements assainissants de la carcasse sur la viabilitĂ© duparasite Toxocara spp., plus particuliĂšrement la congĂ©lation et la cuisson, dans le cas oĂč cestraitements sont rĂ©alisĂ©s, soit par les Ă©tablissements du secteur alimentaire, soit directementpar les consommateurs
    corecore