Neural networks : the official journal of the International Neural Network Society
May 1, 2025
Federated learning (FL) is a research area focusing on model training across numerous users while preserving data privacy under the coordination of a central server. The inherent optimization challenges in FL often manifest as nonconvex and nonsmooth...
Neural networks : the official journal of the International Neural Network Society
May 1, 2025
Binary code similarity detection (BSCD), whose goal is to identify and analyze similar or identical functions in compiled binaries, is an essential task in computer security. Recent methods leveraging deep neural networks (DNN) for numerical vector r...
PURPOSE: Conventional quantitative susceptibility mapping (QSM) methods rely on simplified physical models that assume isotropic and homogeneous tissue properties, leading to artifacts and inaccuracies in biological tissues. This study aims to develo...
Neural networks : the official journal of the International Neural Network Society
May 1, 2025
Machine learning has been extensively applied to signal decoding in electroencephalogram (EEG)-based brain-computer interfaces (BCIs). While most studies have focused on enhancing the accuracy of EEG-based BCIs, more attention should be given to thei...
Effective teacher performance evaluation is important for enhancing the quality of educational systems. This study presents a novel approach that integrates deep learning and metaheuristics to assess the pedagogical quality of English as a foreign la...
Deep neural networks are used to accurately detect, estimate, and predict human body poses in images or videos through deep learning-based human pose estimation. However, traditional multi-person pose estimation methods face challenges due to partial...
International journal of neural systems
Apr 30, 2025
Spiking Neural P Systems are parallel and distributed computational models inspired by biological neurons, emerging from membrane computing and applied to solving computationally difficult problems. This paper focuses on the computational complexity ...
Neural networks : the official journal of the International Neural Network Society
Apr 30, 2025
Automated Machine Learning (AutoML) involves the automatic production of models for specific tasks on given datasets, which can be divided into two aspects: Neural Architecture Search (NAS) for model construction and Hyperparameter Optimization (HPO)...
Neural networks : the official journal of the International Neural Network Society
Apr 30, 2025
Prototype is widely used to represent internal structure of category for few-shot learning, which was proposed as a simple inductive bias to address the issue of overfitting. However, for categories where prototypes do not exist or are difficult to r...
This study developed an effective approach for discriminating geographical origins of Duhuo samples using non-targeted UPLC chromatograms and UV-Vis spectrogram images combined with a two-dimensional convolution neural network (2D-CNN). For compariso...
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