AIMC Journal:
IEEE transactions on neural networks and learning systems

Showing 771 to 780 of 817 articles

EmT: A Novel Transformer for Generalized Cross-Subject EEG Emotion Recognition.

IEEE transactions on neural networks and learning systems Jun 1, 2025
Integrating prior knowledge of neurophysiology into neural network architecture enhances the performance of emotion decoding. While numerous techniques emphasize learning spatial and short-term temporal patterns, there has been a limited emphasis on ...
Databases, Factual Neural Networks, Computer Electroencephalography Algorithms Emotions Humans
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Universal Approximation Theorem and Error Bounds for Quantum Neural Networks and Quantum Reservoirs.

IEEE transactions on neural networks and learning systems Jun 1, 2025
Universal approximation theorems are the foundations of classical neural networks, providing theoretical guarantees that the latter are able to approximate maps of interest. Recent results have shown that this can also be achieved in a quantum settin...
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Learning Sequential Variation Information for Dynamic Facial Expression Recognition.

IEEE transactions on neural networks and learning systems Jun 1, 2025
A multiscale sequence information fusion (MSSIF) method is presented for dynamic facial expression recognition (DFER) in video sequences. It exploits multiscale information by integrating features from individual frames, subsequences, and entire sequ...
Machine Learning Algorithms Humans Neural Networks, Computer Video Recording Pattern Recognition, Automated Automated Facial Recognition Facial Expression
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Self-Organizing Stacked Type-2 Fuzzy Neural Network With Rule Generalization.

IEEE transactions on neural networks and learning systems Jun 1, 2025
Type-2 fuzzy neural networks (T2FNNs) are particularly effective in dealing with nonlinear systems. However, they inevitably suffer from multicollinearity problems caused by the significant overlaps of the footprint uncertainty (FOU), which leads to ...
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Toward Building Human-Like Sequential Memory Using Brain-Inspired Spiking Neural Models.

IEEE transactions on neural networks and learning systems Jun 1, 2025
The brain is able to acquire and store memories of everyday experiences in real-time. It can also selectively forget information to facilitate memory updating. However, our understanding of the underlying mechanisms and coordination of these processe...
Computer Simulation Models, Neurological Action Potentials Neurons Neural Networks, Computer Memory Humans Brain
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Rethinking Appearance-Based Deep Gait Recognition: Reviews, Analysis, and Insights From Gait Recognition Evolution.

IEEE transactions on neural networks and learning systems Jun 1, 2025
Gait recognition is a prominent biometric recognition technique extensively employed in public security. Appearance-based and model-based gait recognition are two categories of methods commonly used. Specifically, appearance-based methods, which use ...
Algorithms Deep Learning Humans Neural Networks, Computer Pattern Recognition, Automated Biometric Identification Gait
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STSF: Spiking Time Sparse Feedback Learning for Spiking Neural Networks.

IEEE transactions on neural networks and learning systems Jun 1, 2025
Spiking neural networks (SNNs) are biologically plausible models known for their computational efficiency. A significant advantage of SNNs lies in the binary information transmission through spike trains, eliminating the need for multiplication opera...
Animals Time Factors Computer Simulation Feedback Humans Action Potentials Machine Learning Neuronal Plasticity Neurons Neural Networks, Computer Algorithms Models, Neurological
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Discovery of Shared Latent Nonlinear Effective Connectivity for EEG-Based Depression Detection.

IEEE transactions on neural networks and learning systems Jun 1, 2025
Granger causality (GC) effective connectivity (EC) calculated from electroencephalogram (EEG) signals has been widely used in mental disorder detection. However, the existing methods only take into account linear dynamics or nonlinear dynamics within...
Depression Neural Networks, Computer Humans Electroencephalography Algorithms Signal Processing, Computer-Assisted Nonlinear Dynamics
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A Forward and Backward Compatible Framework for Few-Shot Class-Incremental Pill Recognition.

IEEE transactions on neural networks and learning systems Jun 1, 2025
Automatic pill recognition (APR) systems are crucial for enhancing hospital efficiency, assisting visually impaired individuals, and preventing cross-infection. However, most existing deep learning-based pill recognition systems can only perform clas...
Neural Networks, Computer Deep Learning Algorithms Pattern Recognition, Automated Humans
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Scale-Aware Super-Resolution Network With Dual Affinity Learning for Lesion Segmentation From Medical Images.

IEEE transactions on neural networks and learning systems Jun 1, 2025
Convolutional neural networks (CNNs) have shown remarkable progress in medical image segmentation. However, the lesion segmentation remains a challenge to state-of-the-art CNN-based algorithms due to the variance in scales and shapes. On the one hand...
Deep Learning Image Processing, Computer-Assisted Machine Learning Algorithms Humans Neural Networks, Computer
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