Analysis of Coherence-Collapse Regime of Semiconductor Lasers Under External Optical Feedback by Perturbation Method

This chapter investigates a preliminary interpretation of the experimental results recently obtained with InAs/InP quantum-dash Fabry-Perot lasers, by using the formalism developed from the so-called asymptotic method

Real-time distance measurement immune from atmospheric parameters using optical frequency combs

We propose a direct and real-time ranging scheme using an optical frequency combs, able to compensate optically for index of refraction variations due to atmospheric parameters. This scheme could be useful for applications requiring stringent precision over a long distance in air, a situation where dispersion becomes the main limitation. The key ingredient is the use of a mode-locked laser as a precise source for multi-wavelength interferometry in a homodyne detection scheme. By shaping temporally the local oscillator, one can directly access the desired parameter (distance) while being insensitive to fluctuations induced by parameters of the environment such as pressure, temperature, humidity and CO$_2$ content

Lasers à boîtes quantiques et tolérance à la rétroaction optique

PARIS-BIUSJ-Physique recherche (751052113) / SudocEVRY-INT (912282302) / SudocSudocFranceF

Application and Comparison of Deep Learning Methods to Detect Night-Time Road Surface Conditions for Autonomous Vehicles

Currently, road surface conditions ahead of autonomous vehicles are not well detected by the existing sensors on those autonomous vehicles. However, driving safety should be ensured for the weather-induced road conditions for day and night. An investigation into deep learning to recognize the road surface conditions in the day is conducted using the collected data from an embedded camera on the front of the vehicles. Deep learning models have only been proven to be successful in the day, but they have not been assessed for night conditions to date. The objective of this work is to propose deep learning models to detect on-line road surface conditions caused by weather ahead of the autonomous vehicles at night with a high accuracy. For this study, different deep learning models, namely traditional CNN, SqueezeNet, VGG, ResNet, and DenseNet models, are applied with performance comparison. Considering the current limitation of existing night-time detection, reflection features of different road surfaces are investigated in this paper. According to the features, night-time databases are collected with and without ambient illumination. These databases are collected from several public videos in order to make the selected models more applicable to more scenes. In addition, selected models are trained based on a collected database. Finally, in the validation, the accuracy of these models to classify dry, wet, and snowy road surface conditions at night can be up to 94%

Relaxation characteristics of quantum-dash-based semiconductor lasers

info:eu-repo/semantics/publishe

Comportement oscillatoire d'une structure émettrice périodique perturbée par une onde électromagnétique

Nous appliquons la théorie semi-classique à la modélisation du comportement d'une structure périodique perturbée par une onde électromagnétique. La dépendance, en polarisation du champ électrique et en localisation du dipôle, de l'oscillation de Rabi ainsi que de la probabilité de transition est analysée

Propriétés d'émission d'une structure périodique – dépendance en polarisation et en localisation de dipôle

Nous résumons quelques résultats de notre modélisation électromagnétique sur une structure active à bande interdite photonique, en mettant l'accent sur la dépendance en polarisation du couplage entre la densité de modes optiques et le champ électrique local ainsi que sur la possibilité de mettre à profit celle-ci pour réaliser une émission à polarisation prédéfinie

Quantitative study of vehicle-pedestrian interactions: Towards pedestrian-adapted lighting communication functions for autonomous vehicles

International audienc

Evaluating the Understandability of Light Patterns and Pictograms for Autonomous Vehicle-to-Pedestrian Communication Functions

International audienc