Publications
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EmoNeXt: an Adapted ConvNeXt for Facial Emotion Recognition
Facial expressions play a crucial role in human communication serving as a powerful and impactful means to express a wide range of emotions. With advancements in artificial intelligence and computer vision, deep neural networks have emerged as effective tools for facial emotion recognition. In this paper, we propose EmoNeXt, a novel deep learning framework for […]
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Machine Learning Assistive State of Charge Estimation of Li-Ion Battery
For an effective and economical deployment of battery-powered electric vehicles, mobile phones, laptops, and medical gadgets, the State of Charge (SoC) of the batteries must be properly assessed. It permits a safe operation, have a longer usable battery life, and prevent malfunctions. In this context, the battery management systems provide diverse SoC estimation solutions. However, […]
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Hybradization of Emperical Mode Decomposition and Machine Learning for Categorization of Cardiac Diseases
The arrhythmia is one of the cardiovascular diseases which has several types. In literature, researchers have presented a broad study on the strategies utilized for Electrocardiogram (ECG) signal investigation. Automated arrhythmia detection by analyzing the ECG data is reported using a number of intriguing techniques and discoveries. In order to effectively categorize arrhythmia, a novel […]
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Artificial Intelligence Assistive Fire Detection and Seeing the Invisible Through Smoke using Hyperspectral and Multi-spectral Images
Abstract— The global warming has serious impact on our climate. Due to this, the frequency and the intensity of forest fires is increasing. It has shown serious challenges such as the protection of resources, human and wild life, health, and property. This study focuses on developing an artificial intelligence assistive innovative solution for active fire […]
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Particle filter meets hybrid octrees: an octree-based ground vehicle localization approach without learning
This paper proposes an accurate lidar-based outdoor localization method that requires few computational resources, is robust in challenging environments (urban, off-road, seasonal variations) and whose performances are equivalent for two different sensor technologies: scanning LiDAR and flash LiDAR. The method is based on the matching between a pre-built 3D map and the LiDAR measurements. Our […]
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Innovation culture in French organisations
The aim of this study was to measure the relative impact of culture and processes on innovation performance. Contrary to processes, culture represents all implicit factors influencing daily behaviour. Culture gathers the unwritten rules of the social game and serves as social cement for an organisation. Processes correspond to identified and formalised practices and rules, […]
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Toward Universal Creativity Assessment by Untrained Judges
The purpose of a creativity session being first to generate many ideas, how to fast and reliably assess each one’s creativity, even with non-creativity experts? Creative people appearing not only to be good at generating ideas but also at implicitly evaluating them, improving people’s assessment would further improve their own creativity. This paper investigates canonical […]
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Developing innovation culture through the transformation of a master learning path
Every year, around one thousands of postgraduate students attends CESI preparing expertise master courses on diverse aspects of management. During this year, MS® postgraduate students work in companies and spend one week per month at CESI. For each student, one of the issue of the year is to write a professional thesis. On student size, […]
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Improving Causality in Interpretable Video Retrieval
This paper focuses on the causal relation between the detection scores of concept (or tag) classifiers and the ranking decisions based on these scores, paving the way for these tags to be used in the visual explanations. We first define a measure for quantifying a causality on a set of tags, typically those involved in […]
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Errare humanum est, perseverare autem diabolicum: A Follow-Up Study on the Human-Likeness of an AI Othello Player
Othello, also known as Reversi, is a popular 2-players board game. Olivaw is an intelligent agent playing Othello. Compared to the most famous ones (such as Saio), it exploits limited resources by autonomously learning how to improve its gameplay by playing against itself. In previous occasions, Othello players reported the impression of a sort of […]
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NSGA-II for solving a multi-objective, sustainable and flexible job shop scheduling problem
Recently, sustainable scheduling has emerged to make the trade-off between economic, environmental and social factors. While classical scheduling research focuses on economic and environmental indicators such as makespan and energy consumption, modern human-centred manufacturing systems consider additional important factors such as workers’ well-being and ergonomic risks. This study proposes a multi-objective mathematical model that jointly […]
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Optimizing Resource Allocation in the Flexible Job Shop Problem: Assessing the Impact of Rest Breaks on Task Strenuousness Reduction
The integration of collaborative robots (cobots) in production workshops aims to enhance productivity while minimizing physical strain for human operators. However, physical strain is often treated merely as a constraint rather than as an objective to address. To effectively model the production process and incorporate human factors, it is crucial to employ an appropriate index […]
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