Search Results for author: Hugues Talbot

Found 10 papers, 6 papers with code

A foundation for exact binarized morphological neural networks

1 code implementation8 Jan 2024 Theodore Aouad, Hugues Talbot

Training and running deep neural networks (NNs) often demands a lot of computation and energy-intensive specialized hardware (e. g. GPU, TPU...).

Binarization

On the detection of Out-Of-Distribution samples in Multiple Instance Learning

1 code implementation11 Sep 2023 Loïc Le Bescond, Maria Vakalopoulou, Stergios Christodoulidis, Fabrice André, Hugues Talbot

While significant efforts have been devoted to OOD detection in classical supervised settings, the context of weakly supervised learning, particularly the Multiple Instance Learning (MIL) framework, remains under-explored.

Multiple Instance Learning Out of Distribution (OOD) Detection +1

Bone mineral density estimation from a plain X-ray image by learning decomposition into projections of bone-segmented computed tomography

1 code implementation21 Jul 2023 Yi Gu, Yoshito Otake, Keisuke Uemura, Mazen Soufi, Masaki Takao, Hugues Talbot, Seiji Okada, Nobuhiko Sugano, Yoshinobu Sato

The proposed method achieved high accuracy in BMD estimation, where Pearson correlation coefficients of 0. 880 and 0. 920 were observed for DXA-measured BMD and QCT-measured BMD estimation tasks, respectively, and the root mean square of the coefficient of variation values were 3. 27 to 3. 79% for four measurements with different poses.

Density Estimation

MSKdeX: Musculoskeletal (MSK) decomposition from an X-ray image for fine-grained estimation of lean muscle mass and muscle volume

no code implementations31 May 2023 Yi Gu, Yoshito Otake, Keisuke Uemura, Masaki Takao, Mazen Soufi, Yuta Hiasa, Hugues Talbot, Seiji Okata, Nobuhiko Sugano, Yoshinobu Sato

We propose a method (named MSKdeX) to estimate fine-grained muscle properties from a plain X-ray image, a low-cost, low-radiation, and highly accessible imaging modality, through musculoskeletal decomposition leveraging fine-grained segmentation in CT. We train a multi-channel quantitative image translation model to decompose an X-ray image into projections of CT of individual muscles to infer the lean muscle mass and muscle volume.

Computed Tomography (CT) Image-to-Image Translation +1

Binary Multi Channel Morphological Neural Network

1 code implementation19 Apr 2022 Theodore Aouad, Hugues Talbot

Neural networks and particularly Deep learning have been comparatively little studied from the theoretical point of view.

Binary Morphological Neural Network

1 code implementation23 Mar 2022 Theodore Aouad, Hugues Talbot

In the last ten years, Convolutional Neural Networks (CNNs) have formed the basis of deep-learning architectures for most computer vision tasks.

Atlas-based automated detection of swim bladder in Medaka embryo

no code implementations16 Feb 2019 Diane Genest, Marc Léonard, Jean Cousty, Noémie De Crozé, Hugues Talbot

An automated random forest clas-sifier is built from these descriptors in order to classify embryos with and without a swim bladder.

Bladder Segmentation Segmentation

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