58 citations · 181 across the 29 of their papers we have counts for
32 papers
Segment-Level Risk Discovery in Online Handwriting for Alzheimer's Disease Detection
Changqing Gong, Huafeng Qin, Mounîm A. El-Yacoubi
Online handwriting provides a non-invasive and low-cost behavioral biomarker for Alzheimer's disease (AD) detection, as it reflects both cognitive planning and fine motor control.…
Profiling Handwriting-Process Deviations in Developmental Dysgraphia: An Open, Normatively-Referenced Instrument
Jihyun Mun, Mounîm A. El-Yacoubi
Online handwriting captured on digitizing tablets yields hundreds of kinematic, temporal, spatial, and dynamic features. These features are rarely organized into interpretable, reu…
Real-Time Design of Public Transport Lines: Reconciling Adaptivity and Efficiency
Duo Wang, Andrea Araldo, Mounim El-Yacoubi
Demand-responsive transport (DRT) is typically routed by solving Dynamic Vehicle Routing Problems (DVRPs), where individual vehicle trajectories are adjusted on incoming requests.…
Predict-then-Optimize Framework for Public Transport Line Redesign under Fluctuating Traffic Conditions
Zihao Guo, Andrea Araldo, Faycal Touzout +1
Public Transport (PT) lines are traditionally designed to optimize performance under nominal traffic conditions. In practice, operating conditions frequently deviate from nominal o…
Physiological Prior-Driven Label Enhancement for Cross-Subject EEG Emotion Recognition
Hongyu Zhu, Lin Chen, Yuming Fu +2
Electroencephalography (EEG)-based emotion recognition captures affective neural signals with high temporal precision, but cross-subject variability and label noise remain critical…
Cross-Task Generalization in Handwriting-Based Alzheimer's Screening via Vision Language Adaptation
Changqing Gong, Huafeng Qin, Mounim A. El-Yacoubi
Alzheimer's disease (AD) is a prevalent neurodegenerative disorder for which early detection is critical. Handwriting, which can be disrupted by subtle motor and cognitive decline,…
MS-Mix: Sentiment-Guided Adaptive Augmentation for Multimodal Sentiment Analysis
Hongyu Zhu, Lin Chen, Xin Jin +1
Multimodal Sentiment Analysis (MSA) integrates complementary features from text, video, and audio for robust emotion understanding in human interactions. However, models suffer fro…
MMSE-Calibrated Few-Shot Prompting for Alzheimer's Detection
Jana Sweidan, Mounim A. El-Yacoubi, Nasredine Semmar
Prompting large language models is a training-free method for detecting Alzheimer's disease from speech transcripts. Using the ADReSS dataset, we revisit zero-shot prompting and st…
Frame Sampling Strategies Matter: A Benchmark for small vision language models
Marija Brkic, Anas Filali Razzouki, Yannis Tevissen +2
Comparing vision language models on videos is particularly complex, as the performances is jointly determined by the model's visual representation capacity and the frame-sampling s…
Polar Coordinate-Based 2D Pose Prior with Neural Distance Field
Qi Gan, Sao Mai Nguyen, Eric Fenaux +2
Human pose capture is essential for sports analysis, enabling precise evaluation of athletes' movements. While deep learning-based human pose estimation (HPE) models from RGB video…
Hybrid Transformer for Early Alzheimer's Detection: Integration of Handwriting-Based 2D Images and 1D Signal Features
Changqing Gong, Huafeng Qin, Mounîm A. El-Yacoubi
Alzheimer's Disease (AD) is a prevalent neurodegenerative condition where early detection is vital. Handwriting, often affected early in AD, offers a non-invasive and cost-effectiv…
Online design of dynamic networks
Duo Wang, Andrea Araldo, Mounim El Yacoubi
Designing a network (e.g., a telecommunication or transport network) is mainly done offline, in a planning phase, prior to the operation of the network. On the other hand, a massiv…
Relax DARTS: Relaxing the Constraints of Differentiable Architecture Search for Eye Movement Recognition
Hongyu Zhu, Xin Jin, Hongchao Liao +3
Eye movement biometrics is a secure and innovative identification method. Deep learning methods have shown good performance, but their network architecture relies on manual design…
Neural Architecture Search based Global-local Vision Mamba for Palm-Vein Recognition
Huafeng Qin, Yuming Fu, Jing Chen +3
Due to the advantages such as high security, high privacy, and liveness recognition, vein recognition has been received more and more attention in past years. Recently, deep learni…
EM-DARTS: Hierarchical Differentiable Architecture Search for Eye Movement Recognition
Huafeng Qin, Hongyu Zhu, Xin Jin +3
Eye movement biometrics has received increasing attention thanks to its highly secure identification. Although deep learning (DL) models have shown success in eye movement recognit…
MsMemoryGAN: A Multi-scale Memory GAN for Palm-vein Adversarial Purification
Huafeng Qin, Yuming Fu, Huiyan Zhang +4
Deep neural networks have recently achieved promising performance in the vein recognition task and have shown an increasing application trend, however, they are prone to adversaria…
SUMix: Mixup with Semantic and Uncertain Information
Huafeng Qin, Xin Jin, Hongyu Zhu +3
Mixup data augmentation approaches have been applied for various tasks of deep learning to improve the generalization ability of deep neural networks. Some existing approaches CutM…
StarLKNet: Star Mixup with Large Kernel Networks for Palm Vein Identification
Xin Jin, Hongyu Zhu, Mounîm A. El Yacoubi +4
As a representative of a new generation of biometrics, vein identification technology offers a high level of security and convenience.Convolutional neural networks (CNNs), a promin…
Adversarial Masking Contrastive Learning for vein recognition
Huafeng Qin, Yiquan Wu, Mounim A. El-Yacoubi +2
Vein recognition has received increasing attention due to its high security and privacy. Recently, deep neural networks such as Convolutional neural networks (CNN) and Transformers…
EmMixformer: Mix transformer for eye movement recognition
Huafeng Qin, Hongyu Zhu, Xin Jin +3
Eye movement (EM) is a new highly secure biometric behavioral modality that has received increasing attention in recent years. Although deep neural networks, such as convolutional…
Adversarial AutoMixup
Huafeng Qin, Xin Jin, Yun Jiang +2
Data mixing augmentation has been widely applied to improve the generalization ability of deep neural networks. Recently, offline data mixing augmentation, e.g. handcrafted and sal…
Exploring Emotion Expression Recognition in Older Adults Interacting with a Virtual Coach
Cristina Palmero, Mikel deVelasco, Mohamed Amine Hmani +18
The EMPATHIC project aimed to design an emotionally expressive virtual coach capable of engaging healthy seniors to improve well-being and promote independent aging. One of the cor…
AccEq-DRT: Planning Demand-Responsive Transit to reduce inequality of accessibility
Duo Wang, Andrea Araldo, Mounim A. El Yacoubi
Accessibility measures how well a location is connected to surrounding opportunities. We focus on accessibility provided by Public Transit (PT). There is an evident inequality in t…
Integration of Clinical Criteria into the Training of Deep Models: Application to Glucose Prediction for Diabetic People
Maxime De Bois, Mounîm A. El Yacoubi, Mehdi Ammi
Standard objective functions used during the training of neural-network-based predictive models do not consider clinical criteria, leading to models that are not necessarily clinic…