Search results for "artificial intelligence"

Leveraging Uncertainty Estimates to Improve Segmentation Performance in Cardiac MR

2021

International audience; In medical image segmentation, several studies have used Bayesian neural networks to segment and quantify the uncertainty of the images. These studies show that there might be an increased epistemic uncertainty in areas where there are semantically and visually challenging pixels. The uncertain areas of the image can be of a great interest as they can possibly indicate the regions of incorrect segmentation. To leverage the uncertainty information, we propose a segmentation model that incorporates the uncertainty into its learning process. Firstly, we generate the uncertainty estimate (sample variance) using Monte-Carlo dropout during training. Then we incorporate it …

Système de sécurité biométrique multimodal par imagerie, dédié au contrôle d’accès

2019

Research of this thesis consists in setting up efficient and light solutions to answer the problems of securing sensitive products. Motivated by a collaboration with various stakeholders within the Nuc-Track project, the development of a biometric security system, possibly multimodal, will lead to a study on various biometric features such as the face, fingerprints and the vascular network. This thesis will focus on an algorithm and architecture matching, with the aim of minimizing the storage size of the learning models while guaranteeing optimal performances. This will allow it to be stored on a personal support, thus respecting privacy standards.

DPLL with restarts linearly simulates CDCL

2019

If we give DPLL the ability to make restarts and to learn clauses representing the explored search space, it can linearly simulate CDCL solvers.

Automatic Timeline Construction and Analysis For Computer Forensics Purposes

2014

International audience; To determine the circumstances of an incident, investigators need to reconstruct events that occurred in the past. The large amount of data spread across the crime scene makes this task very tedious and complex. In particular, the analysis of the reconstructed timeline, due to the huge quantity of events that occurred on a digital system, is almost impossible and leads to cognitive overload. Therefore, it becomes more and more necessary to develop automatic tools to help or even replace investigators in some parts of the investigation. This paper introduces a multi-layered architecture designed to assist the investigative team in the extraction of information left in…

6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty

2001

International audience; no abstract

Actes CNIA 2018 - Conférence Nationale d'Intelligence Artificielle

2018

Sub-optimal waypoints, UAV path planning and mosaicing application

2016

International audience; Create a complete system of video surveillance using camera mounted on a robot like UAV to maintain optimized vast area coverage and reconstruct an image by using mosaicing techniques. This paper demonstrated the efficiency of using one UAV to cover vast area using optimized positions.

Research and implementation of artificial neural networks models for high velocity oxygen fuel thermal spraying

2020

In the high velocity oxygen fuel (HVOF) spray process, the coating properties are sensitive to the characteristics of in-flight particles, which are mainly determined by the process parameters. Due to the complex chemical and thermodynamic reactions during the deposition procedure, obtaining a comprehensive multi-physical model or analytical analysis of the HVOF process is still a challenging issue. This study proposes to develop a robust methodology via artificial neural networks (ANN) to solve this problem for the HVOF sprayed NiCr-Cr3C2 coatings under different operating parameters.First, 40 sets of HVOF spray experiments were conducted and the coating properties were tested for analysis…

Semantic User Profiling for Digital Advertising

2015

International audience; With the emergence of real-time distribution of online advertising space (“real-time bidding”), user profiling from web navigation traces becomes crucial. Indeed, it allows online advertisers to target customers without interfering with their activities. Current techniques apply traditional methods as statistics and machine learning, but suffer from their limitations. As an answer, the proposed approach aims to develop and evaluate a semantic-based user profiling system for digital advertising.

TOWARDS SEMANTIC INTEROPERABILITY FOR ENTERPRISE INFORMATION SYSTEMS

2016

International audience; In the context of globalisation, data and knowledge management, and given the need to deliver a quick response to changes in market forces, enterprises have to collaborate using information technologies to succeed in a disparate and dynamical business environment. Enterprise interoperability (EI) is a field of study that aims to improve this collaboration. Moreover, EI addresses problems related to the lack of system interoperability in organisations. In this paper, we focus on approaches which deliver semantic interoperability among enterprise information systems. We conclude by identifying the main drawbacks of such approaches to be adopted by world-wide industry a…