Gilles Henaff

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In this work, we present an extended study of image representations for fine-grained classification with respect to image resolution. Understudied in literature, this parameter yet presents many practical and theoretical interests, e.g. in embedded systems where restricted computational resources prevent treating high-resolution images. It is thus(More)
In the present study the fatigue crack propagation resistance of a nearly fully lamellar quaternary TiAl based is investigated at room-temperature. The fatigue crack growth rates material are shown to be highly sensitive on the applied stress intensity factor amplitude. A special attention is also paid to the influence of extrinsic factors. Thus(More)
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(More)
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