Search results for "Signal and Image processing"

Visual and acoustic techniques for motorcycle collision warning system with EEG validation

2018

In many countries, motorcyclist fatality rate is much higher than that of other vehicle drivers. Among many other factors, motorcycle rear-end collisions are also contributing to these biker fatalities. Collision detection systems can be used to minimize these fatalities. However, most of the existing collision detection systems do not identify the type of potential hazard faced by motorcyclists. Every collision warning system used a distinctive collision detection technique, which limits its performance and makes it imperative to study its effectiveness. Unfortunately, no such work has been reported in that particular domain for motorcyclists. Therefore, it is important to study the physio…

Electrophysiological Effects of Direct Electrical Stimulations During Awake Brain Surgery: Methodological Considerations

2015

International audience; IRECT electrical stimulation (DES) has long been used to perform real-time functional mapping of the brain. More recently, this technique was introduced in the neurosurgery of slow-growing and infiltrative brain tumors to guide the resection with great success. By generating transient perturbations, this method allows the real-time identification of both cortical areas and subcortical networks that are essential for the function. Thus, as much as possible, non-functional tissue can be removed while minimizing the sequelae. However, the understanding of the electrophysiological effects of DES and, in particular its remote propagation, remains an open and key question.…

Visual-auditory substitution device for indoor navigation based on fast visual marker detection

2022

Design of ADAS Fatigue Control System using Pynq z1 and Jetson Xavier NX

2022

An Optimised Indoor Deployment of Visual Sensor Networks

2022

A starting point for real-time human action detection

2019

Analyzing videos of human actions involves understanding the spatial and temporal context of the scenes. State-of-the-art approaches have demonstrated impressive results using Convolution Neural Networks (CNNs). However, most of them operate in a non-real-time, offline fashion and are not well-equipped for many emerging real-world scenarios, such as autonomous driving and public surveillance. In addition, they are computationally demanding to be deployed on devices with limited power resources (e.g., embedded systems). This paper reviews state-of-the-art methods based on CNN for human action detection and related topics. Following that, we propose an initial framework to efficiently address…

Comparative study of deep learning and classical methods applied to face authentication in context of high constraints application

2018

International audience

Low-noise and low power photoreceptor using split-length MSOFET

2019

International audience

Real-Time Temporal Superpixels for Unsupervised remote photopletysmography

2018

International audience

Towards automated and operational forest inventories with T-Lidar

2011

International audience; Forest inventory automation has become a major issue in forestry. The complexity of the segmentation of 3D point cloud is due to mutual occlusion between trees, other vegetation, or branches. That is why, the applications done until now are limited to the estimation of the DBH (Diameter at Breast Height), the tree height and density estimation. Furthermore other parameters could also be detected, such as volume or species of trees (Reulke and Haala) . . . This paper presents an effective approach for automatic detection, isolation of trees and DBH estimation. Tree isolation is achieved using an innovative approach based on a clustering methodology followed by a skele…