Publications
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CAPSULE TRANSFORMER NETWORK FOR DYNAMIC HAND GESTURE RECOGNITION USING MULTIMODAL DATA
In recent years, deep learning techniques have achieved remarkable success in video analysis and more especially in action and gesture recognition. Even though convolutional neural networks (CNNs) remain the most widely used models, they have difficulty in capturing the global contextual information involving spatial and temporal domains or intermodality due to the local feature learning […]
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Fully Residual Unet-based Semantic Segmentation of Automotive Fisheye Images: a Comparison of Rectangular and Deformable Convolutions
Semantic image segmentation is an essential task for autonomous vehicles and self-driving cars where a complete and real-time perception of the surroundings is mandatory. Convolutional Neural Network approaches for semantic segmentation standout over other state-of-the-art solutions due to their powerful generalization ability over unknown data and end-to-end training. Fisheye images are important due to their […]
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Forecasting photovoltaic energy for a winter house using a Hybrid Deep Learning Model
As part of the energy transition, controlling energy consumption is a challenge for everyone. To this end, a number of sustainable solutions are being proposed, notably for BIPV (Building Integrated Photovoltaics) buildings. In addition, artificial intelligence (AI) is an effective tool for analyzing photovoltaic (PV) energy production and consumption data. It will then be possible […]
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Machine Learning and Feature Ranking for Impact Fall Detection Event Using Multisensor Data
Falls among individuals, especially the elderly population, can lead to serious injuries and complications. Detecting impact moments within a fall event is crucial for providing timely assistance and minimizing the negative consequences. In this work, we aim to address this challenge by applying thorough preprocessing techniques to the multisensor dataset, the goal is to eliminate […]
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MR-STGN: Multi-Residual Spatio Temporal Graph Network using Attention Fusion for Patient Action Assessment
Accurate assessment of patient actions plays a crucial role in healthcare as it contributes significantly to disease progression monitoring and treatment effectiveness. However, traditional approaches to assess patient actions often rely on manual observation and scoring, which are subjective and time-consuming. In this paper, we propose an automated approach for patient action assessment using a […]
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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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