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20132025
most cited3D CNN-based classification using sMRI and MD-DTI images for Alzheimer disease studies

72 citations · 97 across the 10 of their papers we have counts for

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10 papers · 1 filter

cs.CV2025

Identifying Surgical Instruments in Laparoscopy Using Deep Learning Instance Segmentation

Sabrina Kletz, Klaus Schoeffmann, Jenny Benois-Pineau +1

Recorded videos from surgeries have become an increasingly important information source for the field of medical endoscopy, since the recorded footage shows every single detail of…

cs.CV2022

3D Convolutional Networks for Action Recognition: Application to Sport Gesture Recognition

Pierre-Etienne Martin, J Benois-Pineau, R Péteri +2

3D convolutional networks is a good means to perform tasks such as video segmentation into coherent spatio-temporal chunks and classification of them with regard to a target taxono…

cs.CV2021★ 2 cited

Sports Video: Fine-Grained Action Detection and Classification of Table Tennis Strokes from Videos for MediaEval 2021

Pierre-Etienne Martin, Jordan Calandre, Boris Mansencal +4

Sports video analysis is a prevalent research topic due to the variety of application areas, ranging from multimedia intelligent devices with user-tailored digests up to analysis o…

cs.CV2021★ 13 cited

Three-Stream 3D/1D CNN for Fine-Grained Action Classification and Segmentation in Table Tennis

Pierre-Etienne Martin, Jenny Benois-Pineau, Renaud Péteri +1

This paper proposes a fusion method of modalities extracted from video through a three-stream network with spatio-temporal and temporal convolutions for fine-grained action classif…

cs.CV2021

White Box Methods for Explanations of Convolutional Neural Networks in Image Classification Tasks

Meghna P Ayyar, Jenny Benois-Pineau, Akka Zemmari

In recent years, deep learning has become prevalent to solve applications from multiple domains. Convolutional Neural Networks (CNNs) particularly have demonstrated state of the ar…

cs.CV2020

3D attention mechanism for fine-grained classification of table tennis strokes using a Twin Spatio-Temporal Convolutional Neural Networks

Pierre-Etienne Martin, Jenny Benois-Pineau, Renaud Péteri +1

The paper addresses the problem of recognition of actions in video with low inter-class variability such as Table Tennis strokes. Two stream, "twin" convolutional neural networks a…