Neural networks : the official journal of the International Neural Network Society
Apr 23, 2025
Linking cellular-level phenomena to brain architecture and behavior is a holy grail for theoretical and computational neuroscience. Advances in neuroinformatics have recently allowed scientists to embed spiking neural networks of the cerebellum with ...
Neural networks : the official journal of the International Neural Network Society
Apr 23, 2025
Current few-shot image classification methods encounter challenges in extracting multi-view features that can complement each other and selecting optimal features for classification in a specific task. To address this problem, we propose a novel Task...
Neural networks : the official journal of the International Neural Network Society
Apr 23, 2025
Recently, Transformer-based and multilayer perceptron (MLP) based architectures have formed a competitive landscape in the field of time series forecasting. There is evidence that series decomposition can further enhance the model's ability to percei...
Neural networks : the official journal of the International Neural Network Society
Apr 23, 2025
Continual learning (CL) studies the problem of learning a single model from a sequence of disjoint tasks. The main challenge is to learn without catastrophic forgetting, a scenario in which the model's performance on previous tasks degrades significa...
Computer methods and programs in biomedicine
Apr 23, 2025
BACKGROUND AND OBJECTIVE: This study introduces multiscale feature learning to develop more robust and resilient activity recognition algorithms, aimed at accurately tracking and quantifying rehabilitation exercises while minimizing performance dispa...
Journal of applied clinical medical physics
Apr 23, 2025
BACKGROUND: Tumor segmentation is crucial for lung disease diagnosis and treatment. Most existing deep learning-based automatic segmentation methods rely on manually annotated data for network training.
As the challenge of climate change continues to grow, we need creative solutions to predict better and track industrial waste carbon emissions, focusing on sustainable waste management practices. The present study proposes a state-of-the-art Metavers...
The underlying time-variant and subject-specific brain dynamics lead to inconsistent distributions in electroencephalogram (EEG) topology and representations within and between individuals. However, current works primarily align the distributions of ...
The neural activity patterns of localized brain regions are crucial for recognizing brain intentions. However, existing electroencephalogram (EEG) decoding models, especially those based on deep learning, predominantly focus on global spatial feature...
Many previous works on wearable soft exosuits have primarily focused on assisting human motion, while overlooking safety concerns during movement. This article introduces a novel single-motor, altering bi-directional transfer soft exosuit based on im...
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