Search results for "artificial intelligence"
showing 10 items of 6122 documents
Improving Video Object Detection by Seq-Bbox Matching
2019
International audience
Can SegFormer be a True Competitor to U-Net for Medical Image Segmentation?
2023
The U-Net model, introduced in 2015, is established as the state-of-the-art architecture for medical image segmentation, along with its variants UNet++, nnU-Net, V-Net, etc. Vision transformers made a breakthrough in the computer vision world in 2021. Since then, many transformer based architectures or hybrid architectures (combining convolutional blocks and transformer blocks) have been proposed for image segmentation, that are challenging the predominance of U-Net. In this paper, we ask the question whether transformers could overtake U-Net for medical image segmentation. We compare SegFormer, one of the most popular transformer architectures for segmentation, to U-Net using three publicl…
Nouveau modèle d'intelligence artificielle pour l'optimisation de la mobilité
2017
Toward Artificial Intuition
2019
Contributeurs au Grand Débat National demandant un développement des pistes cyclables dans l'Hérault
2021
Le Grand Débat National, décidé par Emmanuel Macron début 2019 pour répondre au mouvement social des Gilets Jaunes, a permis de collecter les contributions de citoyens sur la transition écologique via une plateforme en ligne. Dans cet article, nous exploitons le corpus constitué par ces contributions pour identifier des zones où les participants demandent le développement de pistes cyclables et d’équipements ferroviaires. Pour cela, nous avons créé un modèle de classification permettant d’identifier les contributions traitant de la thématique du transport et proposé une méthode d’extraction de motifs traduisant les propositions des contributeurs. A l’aide des codes postaux donnés par les co…
Contributeurs au Grand Débat National demandant un développement des pistes cyclables dans l'aire urbaine de Dijon
2020
Le Grand Débat National, décidé par Emmanuel Macron début 2019 pour répondre au mouvement social des Gilets Jaunes, a permis de collecter les contributions de citoyens sur la transition écologique via une plateforme en ligne. Dans cet article, nous exploitons le corpus constitué par ces contributions pour identifier des zones où les participants demandent le développement de pistes cyclables et d’équipements ferroviaires. Pour cela, nous avons créé un modèle de classification permettant d’identifier les contributions traitant de la thématique du transport et proposé une méthode d’extraction de motifs traduisant les propositions des contributeurs. A l’aide des codes postaux donnés par les co…
Event-Based Trajectory Prediction Using Spiking Neural Networks
2021
International audience; In recent years, event-based sensors have been combined with spiking neural networks (SNNs) to create a new generation of bio-inspired artificial vision systems. These systems can process spatio-temporal data in real time, and are highly energy efficient. In this study, we used a new hybrid event-based camera in conjunction with a multi-layer spiking neural network trained with a spike-timing-dependent plasticity learning rule. We showed that neurons learn from repeated and correlated spatio-temporal patterns in an unsupervised way and become selective to motion features, such as direction and speed. This motion selectivity can then be used to predict ball trajectory…
Using Polynomial Loss and Uncertainty Information for Robust Left Atrial and Scar Quantification and Segmentation
2022
Automatic and accurate segmentation of the left atrial (LA) cavity and scar can be helpful for the diagnosis and prognosis of patients with atrial fibrillation. However, automating the segmentation can be difficult due to the poor image quality, variable LA shapes, and small discrete regions of LA scars. In this paper, we proposed a fully-automatic method to segment LA cavity and scar from Late Gadolinium Enhancement (LGE) MRIs. For the loss functions, we propose two different losses for each task. To enhance the segmentation of LA cavity from the multicenter dataset, we present a hybrid loss that leverages Dice loss with a polynomial version of cross-entropy loss (PolyCE). We also utilize …
Artificial Potential Field Simulation Framework for Semi-Autonomous Car Conception
2017
International audience; Artificial potential field is investigated to provide a high level of synergy between driver and semi-autonomous vehicle. This article presents a framework developed to test the performances of this approach. Stand-alone performances of this system is tested for a lane keeping and cruise control application. Performances are promising and future development is discussed.
Some Computational Aspects of DISTANCE-SAT
2007
In many AI fields, one must face the problem of finding a solution that is as close as possible to a given configuration. This paper addresses this problem in a propositional framework. We introduce the decision problem distance-sat, which consists in determining whether a propositional formula admits a model that disagrees with a given partial interpretation on at most d variables. The complexity of distance-sat and of several restrictions of it are identified. Two algorithms based on the well-known Davis/Logemann/Loveland search procedure for the satisfiability problem sat are presented so as to solve distance-sat for CNF formulas. Their computational behaviors are compared with the ones …