Jesús Angulo | DeepAI

DeepAI AI Chat

Featured Co-authors

Zhiyuan Liu
189 publications
Jürgen Schmidhuber
83 publications
Dino Sejdinovic
65 publications
Angela Yao
51 publications
Isabelle Bloch
33 publications
Jonathan Masci
30 publications
Nina Miolane
22 publications
Guillaume Noyel
17 publications
Gianni Franchi
16 publications
Santiago Velasco-Forero
15 publications
Gabriele Corso
11 publications

∙ 01/23/2023

Adapting the Hypersphere Loss Function from Anomaly Detection to Anomaly Segmentation

We propose an incremental improvement to Fully Convolutional Data Descri...

0 João P C Bertoldo, et al. ∙

∙ 11/07/2022

Moving Frame Net: SE(3)-Equivariant Network for Volumes

Equivariance of neural networks to transformations helps to improve thei...

0 Mateus Sangalli, et al. ∙

∙ 10/10/2022

Scale Equivariant U-Net

In neural networks, the property of being equivariant to transformations...

0 Mateus Sangalli, et al. ∙

∙ 07/18/2022

Fully trainable Gaussian derivative convolutional layer

The Gaussian kernel and its derivatives have already been employed for C...

0 Valentin Penaud--Polge, et al. ∙

∙ 07/13/2022

MorphoActivation: Generalizing ReLU activation function by mathematical morphology

This paper analyses both nonlinear activation functions and spatial max-...

0 Santiago Velasco-Forero, et al. ∙

∙ 05/12/2022

Near out-of-distribution detection for low-resolution radar micro-Doppler signatures

Near out-of-distribution detection (OOD) aims at discriminating semantic...

22 Martin Bauw, et al. ∙

∙ 08/22/2021

ICLR 2021 Challenge for Computational Geometry Topology: Design and Results

This paper presents the computational challenge on differential geometry...

0 Nina Miolane, et al. ∙

∙ 06/14/2021

Learning Deep Morphological Networks with Neural Architecture Search

Deep Neural Networks (DNNs) are generated by sequentially performing lin...

8 Yufei Hu, et al. ∙

∙ 02/19/2021

Going beyond p-convolutions to learn grayscale morphological operators

Integrating mathematical morphology operations within deep neural networ...

5 Alexandre Kirszenberg, et al. ∙

∙ 10/02/2020

Morphological segmentation of hyperspectral images

The present paper develops a general methodology for the morphological s...

0 Guillaume Noyel, et al. ∙

∙ 07/31/2020

Fast computation of all pairs of geodesic distances

Computing an array of all pairs of geodesic distances between the pixels...

0 Guillaume Noyel, et al. ∙

∙ 10/28/2019

Multivariate mathematical morphology for DCE-MRI image analysis in angiogenesis studies

We propose a new computer aided detection framework for tumours acquired...

38 Guillaume Noyel, et al. ∙

∙ 03/20/2019

Part-based approximations for morphological operators using asymmetric auto-encoders

This paper addresses the issue of building a part-based representation o...

0 Bastien Ponchon, et al. ∙

∙ 03/19/2019

Max-plus Operators Applied to Filter Selection and Model Pruning in Neural Networks

Following recent advances in morphological neural networks, we propose t...

0 Yunxiang Zhang, et al. ∙

∙ 05/30/2016

Hyperspectral Image Classification with Support Vector Machines on Kernel Distribution Embeddings

We propose a novel approach for pixel classification in hyperspectral im...

0 Gianni Franchi, et al. ∙

∙ 02/09/2016

A New Spatio-Spectral Morphological Segmentation For Multi-Spectral Remote-Sensing Images

A general framework of spatio-spectral segmentation for multi-spectral i...

0 Guillaume Noyel, et al. ∙

∙ 02/02/2016

On distances, paths and connections for hyperspectral image segmentation

The present paper introduces the η and η connections in order to add reg...

0 Guillaume Noyel, et al. ∙

∙ 12/11/2012

A Learning Framework for Morphological Operators using Counter-Harmonic Mean

We present a novel framework for learning morphological operators using ...

0 Jonathan Masci, et al. ∙