AIMC Topic: Neural Networks, Computer

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GQEO: Nearest neighbor graph-based generalized quadrilateral element oversampling for class-imbalance problem.

Neural networks : the official journal of the International Neural Network Society
The class imbalance problem is one of the difficult factors affecting the performance of traditional classifiers. The oversampling technique is the most common way to solve the class imbalance problem. They alleviate the performance impact of the cla...

Chaotic recurrent neural networks for brain modelling: A review.

Neural networks : the official journal of the International Neural Network Society
Even in the absence of external stimuli, the brain is spontaneously active. Indeed, most cortical activity is internally generated by recurrence. Both theoretical and experimental studies suggest that chaotic dynamics characterize this spontaneous ac...

Overfit detection method for deep neural networks trained to beamform ultrasound images.

Ultrasonics
Deep neural networks (DNNs) have remarkable potential to reconstruct ultrasound images. However, this promise can suffer from overfitting to training data, which is typically detected via loss function monitoring during an otherwise time-consuming tr...

RePaIR: Repaired pruning at initialization resilience.

Neural networks : the official journal of the International Neural Network Society
Over the past decade, the size of neural network models has gradually increased in both breadth and depth, leading to a growing interest in the application of neural network pruning. Unstructured pruning provides fine-grained sparsity and achieves be...

Emotion recognition using multi-scale EEG features through graph convolutional attention network.

Neural networks : the official journal of the International Neural Network Society
Emotion recognition via electroencephalogram (EEG) signals holds significant promise across various domains, including the detection of emotions in patients with consciousness disorders, assisting in the diagnosis of depression, and assessing cogniti...

Improving robustness by action correction via multi-step maximum risk estimation.

Neural networks : the official journal of the International Neural Network Society
Certifying robustness against external uncertainties throughout the control process to reduce the risk of instability is very important. Most existing approaches based on adversarial learning use a fixed parameter to adjust the intensity of adversari...

Development and external validation of a multi-task feature fusion network for CTV segmentation in cervical cancer radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Accurate segmentation of the clinical target volume (CTV) is essential to deliver an effective radiation dose to tumor tissues in cervical cancer radiotherapy. Also, although automated CTV segmentation can reduce oncologists' ...

An integrated fuzzy neural network model for surgical approach selection using double hierarchy linguistic information.

Computers in biology and medicine
The selection of the most effective surgical approach is a critical decision in major surgery. With several approaches available, it is important to select the one that will have the most beneficial effect on the patient's health. Multi criteria deci...

BiGM-lncLoc: Bi-level Multi-Graph Meta-Learning for Predicting Cell-Specific Long Noncoding RNAs Subcellular Localization.

Interdisciplinary sciences, computational life sciences
The precise spatiotemporal expression of long noncoding RNAs (lncRNAs) plays a pivotal role in biological regulation, and aberrant expression of lncRNAs in different subcellular localizations has been intricately linked to the onset and progression o...

Domain-guided conditional diffusion model for unsupervised domain adaptation.

Neural networks : the official journal of the International Neural Network Society
Limited transferability hinders the performance of a well-trained deep learning model when applied to new application scenarios. Recently, Unsupervised Domain Adaptation (UDA) has achieved significant progress in addressing this issue via learning do...