Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40040039
Depression is a widespread mental health issue requiring efficient automated detection methods. Traditional single-modality approaches are less effective due to the disorder's complexity, leading to a focus on multimodal analysis. Recent advancements...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039876
This study assesses the performance of different cross-validation splits for brain-signal-based Auditory Attention Decoding (AAD) using deep neural networks on three publicly available Electroencephalography datasets. We investigate the effect of tri...
Neural networks : the official journal of the International Neural Network Society
40101557
Benefiting from the booming development of Transformer methods, the performance of lane detection tasks has been rapidly improved. However, due to the influence of inaccurate lane line shape constraints, the query sequences of existing transformer-ba...
Neural networks : the official journal of the International Neural Network Society
40101555
Convolutional neural networks (CNNs) can effectively extract local features, while Vision Transformer excels at capturing global features. Combining these two networks to enhance the classification performance of hyperspectral images (HSI) has garner...
Autism spectrum disorder (ASD) is a neurodevelopmental condition that affects a child's cognitive and social skills, often diagnosed only after symptoms appear around age 2. Leveraging MRI for early ASD detection can improve intervention outcomes. Th...
Neural networks : the official journal of the International Neural Network Society
40090301
Federated learning (FL) enables collaborative model training without direct data sharing, facilitating knowledge exchange while ensuring data privacy. Multimodal federated learning (MFL) is particularly advantageous for decentralized multimodal data,...
Neural networks : the official journal of the International Neural Network Society
40090300
In the context of few-shot classification, the goal is to train a classifier using a limited number of samples while maintaining satisfactory performance. However, traditional metric-based methods exhibit certain limitations in achieving this objecti...
Neural networks : the official journal of the International Neural Network Society
40088832
Land use and land cover (LULC) classification is a popular research area in remote sensing. The information of single-modal data is insufficient for accurate classification, especially in complex scenes, while the complementarity of multi-modal data ...
BACKGROUND: Motion sickness has been a key factor affecting user experience in Virtual Reality (VR) and limiting the development of the VR industry. Accurate detection of Virtual Reality Motion Sickness (VRMS) is a prerequisite for solving the proble...
Freely moving thought is a type of thinking that shifts from one topic to another without any overarching direction or aim. The ability to detect when freely moving thought occurs may help us promote its beneficial outcomes, such as for creative thin...