AIMC Topic: Neural Networks, Computer

Clear Filters Showing 26501 to 26510 of 31376 articles

PhyTransformer: A unified framework for learning spatial-temporal representation from physiological signals.

Neural networks : the official journal of the International Neural Network Society
As a modal of physiological information, electroencephalogram (EEG), surface electromyography (sEMG), and eye tracking (ET) signals are widely used to decode human intention, promoting the development of human-computer interaction systems. Extensive ...

Learning double balancing representation for heterogeneous dose-response curve estimation.

Neural networks : the official journal of the International Neural Network Society
Estimating the individuals' potential response to varying treatment doses is crucial for decision-making in areas such as precision medicine and management science. Most recent studies predict counterfactual outcomes by learning a covariate represent...

Semantic discrete decoder based on adaptive pixel clustering for monocular depth estimation.

Neural networks : the official journal of the International Neural Network Society
Monocular depth estimation (MDE) has long been a popular and challenging task. Currently, mainstream methods mainly include regression methods based on geometric constraints and ordinal regression methods based on discretized depth intervals. However...

Denoising of high-resolution 3D UTE-MR angiogram data using lightweight and efficient convolutional neural networks.

Magnetic resonance imaging
High-resolution magnetic resonance angiography (∼ 50 μm MRA) data plays a critical role in the accurate diagnosis of various vascular disorders. However, it is very challenging to acquire, and it is susceptible to artifacts and noise which limits its...

Physics-informed neural networks involving unsteady friction for transient pipe flow.

Water research
A robust physics-informed neural network (PINN) approach is developed to accurately predict pressure and flow velocity during the water hammer event, while an experimental system is designed to validate the proposed approach further. Compared to forw...

Internal sensory models allow for balance control using muscle spindle acceleration feedback.

Neural networks : the official journal of the International Neural Network Society
Motor control requires sensory feedback, and the nature of this feedback has implications for the tasks of the central nervous system (CNS): for an approximately linear mechanical system (e.g., a freely standing person, a rider on a bicycle), if the ...

Consensus synchronization via quantized iterative learning for coupled fractional-order time-delayed competitive neural networks with input sharing.

Neural networks : the official journal of the International Neural Network Society
This paper presents the D-type distributed iterative learning control protocol to synchronize fractional-order competitive neural networks with time delay within a finite time frame. Firstly, the input sharing strategy of such desired competitive neu...

GCapNet-FSD: A heterogeneous Graph Capsule Network for Few-Shot object Detection.

Neural networks : the official journal of the International Neural Network Society
Few-shot object detection is a challenging task that aims to quickly adapt detectors to detect novel objects with only a minimal number of annotated examples. Although promising results have been achieved, performance still declines significantly whe...

Modeling multi-scale uncertainty with evidence integration for reliable polyp segmentation.

Neural networks : the official journal of the International Neural Network Society
Polyp segmentation is critical in medical image analysis. Traditional methods, while capable of producing precise outputs in well-defined regions, often struggle with blurry or ambiguous areas in medical images, which can lead to errors in clinical d...

Visual reasoning in object-centric deep neural networks: A comparative cognition approach.

Neural networks : the official journal of the International Neural Network Society
Achieving visual reasoning is a long-term goal of artificial intelligence. In the last decade, several studies have applied deep neural networks (DNNs) to the task of learning visual relations from images, with modest results in terms of generalizati...