In remote sensing applications and medical imaging, one of the key points is acquisition, real-time preprocessing storage information. Due to large amount information present in form images or videos, compression these data necessary. Compressed an efficient technique meet this challenge. It consists acquiring a signal, assuming that it can have sparse representation, by using minimum number nonadaptive linear measurements. After compressed process, reconstruction original signal must be...

On 16 March 2020, as a result of the unprecedented global health crisis linked to emergence new form coronavirus (COVID-19), 74 universities France closed their doors, forcing nearly 1.6 million students, well teachers, find solutions and initiatives that could ensure continuity in teaching. In reliance on videoconferencing tools, chat, sharing documents/tutorials/videos/podcasts, use social networks, many ideas have emerged, but no consensus has developed nor common way doing things been...

Cooperative machine learning has many applications, such as data annotation, where an initial model trained with partially labeled is used to predict labels for unseen continuously. Predicted a low confidence value are manually revised allow the be retrained predicted and data. In this paper, we propose alternative approach: training process called Deep Unsupervised Active Learning. Using proposed scheme, classification can incrementally acquire new knowledge during testing phase without...

Single-Sample Face Recognition (SSFR) is a computer vision challenge. In this scenario, there only one example from each individual on which to train the system, making it difficult identify persons in unconstrained environments, mainly when dealing with changes facial expression, posture, lighting, and occlusion. This paper discusses relevance of an original method for SSFR, called Multi-Block Color-Binarized Statistical Image Features (MB-C-BSIF), exploits several kinds features, namely,...

Since the beginning of COVID-19 pandemic, students around world have seen their schooling completely disrupted. Their teachers had to reorganize in a hurry be able give classes synchronously but at distance. Thanks strong political incentives, both national and university levels, many tools been massively deployed: digital learning management systems (e.g. Moodle), collaborative platforms Google Meets, Microsoft Teams Zoom), social networks Facebook Twitter) even telephone. While pandemic...

Since mid-March 2020, due to the COVID-19 pandemic, higher education has been facing a very uncertain situation, despite hasty implementation of information and communication technologies for distance online learning. Hybrid learning, i.e., mixing face-to-face seems be rule in most universities today. In order build post-COVID-19 university education, one that is increasingly digital sustainable, it essential learn from these years health crisis. this context, paper aims identify quantify...

With the immersion of a plethora technological tools in early post-COVID-19 era university education, instructors around world have been at forefront implementing hybrid learning spaces for knowledge delivery. The purpose this experimental study is not only to divert primary use YouTube channel into tool support asynchronous teaching; it also aims provide feedback and suggest steps actions implement their teaching modules ensure students’ access new while promoting engagement satisfaction,...

The operations of digitization, transmission and storage medical data, particularly images, require increasingly effective encoding methods not only in terms compression ratio flow information but also visual quality. At first, there was DCT (discrete cosine transform) then DWT wavelet their associated standards coding image compression. 2nd-generation wavelets seeks to be positioned confronted by the video currently used. It is this context that we suggest a method combining bandelets SPIHT...

In this paper, we propose a new methodology for crack detection and monitoring in concrete structures. This approach is based on multiresolution analysis of sample or specimen material subjected to several types solicitation. The image obtained by ultrasonic investigation processed customized wavelet analyzed at various scales order detect internal cracks initiation. ultimate objective work an automatic type identification scheme convolutional neural networks (CNN). context, propagation can...

The COVID-19 pandemic, which has been destabilizing the world since end of 2019, significant repercussions on not only health but also economy, finances, society, politics, environments, culture and education [...]

Image denoising is a very important step in cryo-transmission electron microscopy (cryo-TEM) and the energy filtering TEM images before 3D tomography reconstruction, as it addresses problem of high noise these images, that leads to loss contained information. High levels contribute particular difficulties alignment required for reconstruction. This paper investigates are acquired with low exposure time, primary objectives enhancing quality low-exposure time improving process. We propose...

Automatic pain recognition from facial expressions is a challenging problem that has attracted significant attention the research community. This article provides comprehensive analysis on topic by comparing some popular and Off-the-Shell CNN (Convolutional Neural Network) architectures, including MobileNet, GoogleNet, ResNeXt-50, ResNet18, DenseNet-161. We use these networks in two distinct modes: stand alone mode or feature extractor mode. In mode, models (i.e., networks) are used for...

Segmentation of brain tumor images, to refine the detection and understanding abnormal masses in brain, is an important research topic medical imaging. This paper proposes a new segmentation method, consisting three main steps, detect lesions using magnetic resonance imaging (MRI). In first step, parts image delineating skull bone are removed, exclude insignificant data. second which contribution this study, particle swarm optimization (PSO) technique applied, block that contains lesions....

A reliable environment perception is a crucial task for autonomous driving, especially in dense traffic areas. Recent improvements and breakthroughs scene understanding intelligent transportation systems are mainly based on deep learning the fusion of different modalities. In this context, we introduce OLIMP: heterOgeneous Multimodal Dataset Advanced EnvIronMent Perception. This first public, multimodal synchronized dataset that includes UWB radar data, acoustic narrow-band data images....

Biomass is an attractive energy source that can be used for production of heat, power, and transport fuels when produced on a sustainable basis, make large contribution to reducing greenhouse gas emissions. Anaerobic digestion (AD) suitable technology organic matter generating bioenergy in the form biogas. This study investigated factors allowing optimization process biogas from wheat straw (WS). The statistical analysis experiments carried out showed ultrasonic processing plays fundamental...

A new end‐to‐end communication system is proposed to increase transmission speed, robustness, and security in order meet the requirements of mobile systems that know an exponentially increasing data amount over time. The design relies on use compressed sensing‐source coding instead supported speech standards actual systems. method allows reducing complexity by using simple quantisation binary encoding, saving resources, encrypting communications without additional costs. performance...