Search results for "Detection"
showing 10 items of 2543 documents
Système de détection d'anomalies d'aspect par la technique PTM
2011
This documentation details the creation of a support system for the detecting visual sur- face anomalies . This work is based on a technique called Polynomial Texture Mapping (PTM). This technique allows to highlight appearance anomalies by varying the position of the light source. It also makes possible the calculation of the surface topography. This system was designed during the first quarter of 2011 in the SYMME laboratory (Laboratory for Materials and Mechatronics), and is a part of the European research program INTERREG IV. This program aims to enhance a strength of economic activity on both sides of the border France - Switzerland : the realization of high-value products (watches, au…
Development of acoustic devices functionalized with cobalt corroles or metalloporphyrines for the detection of carbon monoxide at low concentration
2012
International audience; Progresses in synthetic chemistry methodologies has pushed to develop a large variety of artificial receptors of particular interest for chemical sensor applications. We investigate here the behavior of gas sensors based on surface acoustic wave (SAW) devices. The use of Love waves that are specially sensitive to surface perturbation enables to exploit the molecular recognition processes occurring in non conductive sensing layers of cobalt corroies [5,10,15-Tris(2,6-dichlorophenyl)corrolato]cobalt(III)] for CO detection. We have monitored phase variations of Love-wave-based delay lines under various operation conditions and studied the detection efficiency of a diffe…
Federated Learning for Zero-Day Attack Detection in 5G and Beyond V2X Networks
2023
Deploying Connected and Automated Vehicles (CAVs) on top of 5G and Beyond networks (5GB) makes them vulnerable to increasing vectors of security and privacy attacks. In this context, a wide range of advanced machine/deep learning-based solutions have been designed to accurately detect security attacks. Specifically, supervised learning techniques have been widely applied to train attack detection models. However, the main limitation of such solutions is their inability to detect attacks different from those seen during the training phase, or new attacks, also called zero-day attacks. Moreover, training the detection model requires significant data collection and labeling, which increases th…
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.
Improving Video Object Detection by Seq-Bbox Matching
2019
International audience
Advanced 3D movement analysis algorithms for robust functional capacity assessment.
2017
SummaryObjectives: We developed a novel system for in home functional capacities assessment in frail older adults by analyzing the Timed Up and Go movements. This system aims to follow the older people evolution, potentially allowing a forward detection of motor decompensation in order to trigger the implementation of rehabilitation. However, the pre-experimentations conducted on the ground, in different environments, revealed some problems which were related to KinectTM operation. Hence, the aim of this actual study is to develop methods to resolve these problems.Methods: Using the KinectTM sensor, we analyze the Timed Up and Go test movements by measuring nine spatio-temporal parameters, …
Fast and Robust Face Detection on a Parallel Optimized Architecture implemented on FPGA
2009
In this paper, we present a parallel architecture for fast and robust face detection implemented on FPGA hardware. We propose the first implementation that meets both real-time requirements in an embedded context and face detection robustness within complex backgrounds. The chosen face detection method is the Convolutional Face Finder (CFF) algorithm, which consists of a pipeline of convolution and subsampling operations, followed by a multilayer perceptron. We present the design methodology of our face detection processor element (PE). This methodology was followed in order to optimize our implementation in terms of memory usage and parallelization efficiency. We then built a parallel arch…
Design of a Real-time face detection parallel architecture using High-Level Synthesis
2008
Abstract We describe a High-Level Synthesis implementation of a parallel architecture for face detection. The chosen face detection method is the well-known Convolutional Face Finder (CFF) algorithm, which consists of a pipeline of convolution operations. We rely on dataflow modelling of the algorithm and we use a high-level synthesis tool in order to specify the local dataflows of our Processing Element (PE), by describing in C language inter-PE communication, fine scheduling of the successive convolutions, and memory distribution and bandwidth. Using this approach, we explore several implementation alternatives in order to find a compromise between processing speed and area of the PE. We …
ROBUST ROAD SIGNS SEGMENTATION IN COLOR IMAGES
2012
International audience; This paper presents an efficient method for road signs segmentation in color images. Color segmentation of road signs is a difficult task due to variations in the image acquisition conditions. Therefore, a color constancy algorithm is usually applied prior to segmentation, which increases the computation time. The proposed method is based on a log-chromaticity color space which shows good invariance properties to changing illumination. Thus, the method is simple and fast since it does not require color constancy algorithms. Experiments with a large dataset and comparison with other approaches, show the robustness and accuracy of the method in detecting road signs in …
Road Signs Detection and Reconstruction using Gielis Curves
2012
International audience; Road signs are among the most important navigation tools in transportation systems. The identification of road signs in images is usually based on first detecting road signs location using color and shape information. In this paper, we introduce such a two-stage detection method. Road signs are located in images based on color segmentation, and their corresponding shape is retrieved using a unified shape representation based on Gielis curves. The contribution of our approach is the shape reconstruction method which permits to detect any common road sign shape, i.e. circle, triangle, rectangle and octagon, by a single algorithm without any training phase. Experimental…