AIMC Topic: Neural Networks, Computer

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WormSwin: Instance segmentation of C. elegans using vision transformer.

Scientific reports
The possibility to extract motion of a single organism from video recordings at a large-scale provides means for the quantitative study of its behavior, both individual and collective. This task is particularly difficult for organisms that interact w...

Quantifying disorder one atom at a time using an interpretable graph neural network paradigm.

Nature communications
Quantifying the level of atomic disorder within materials is critical to understanding how evolving local structural environments dictate performance and durability. Here, we leverage graph neural networks to define a physically interpretable metric ...

Transformer-based hand gesture recognition from instantaneous to fused neural decomposition of high-density EMG signals.

Scientific reports
Designing efficient and labor-saving prosthetic hands requires powerful hand gesture recognition algorithms that can achieve high accuracy with limited complexity and latency. In this context, the paper proposes a Compact Transformer-based Hand Gestu...

Explainable multi-task learning improves the parallel estimation of polygenic risk scores for many diseases through shared genetic basis.

PLoS computational biology
Many complex diseases share common genetic determinants and are comorbid in a population. We hypothesized that the co-occurrences of diseases and their overlapping genetic etiology can be exploited to simultaneously improve multiple diseases' polygen...

Improved GWO and its application in parameter optimization of Elman neural network.

PloS one
Traditional neural networks used gradient descent methods to train the network structure, which cannot handle complex optimization problems. We proposed an improved grey wolf optimizer (SGWO) to explore a better network structure. GWO was improved by...

A survey on neural-symbolic learning systems.

Neural networks : the official journal of the International Neural Network Society
In recent years, neural systems have demonstrated highly effective learning ability and superior perception intelligence. However, they have been found to lack effective reasoning and cognitive ability. On the other hand, symbolic systems exhibit exc...

Extreme Early Image Recognition Using Event-Based Vision.

Sensors (Basel, Switzerland)
While deep learning algorithms have advanced to a great extent, they are all designed for frame-based imagers that capture images at a high frame rate, which leads to a high storage requirement, heavy computations, and very high power consumption. Un...

Automated fundus ultrasound image classification based on siamese convolutional neural networks with multi-attention.

BMC medical imaging
Fundus ultrasound image classification is a critical issue in the medical field. Vitreous opacity (VO) and posterior vitreous detachment (PVD) are two common eye diseases, Now, the diagnosis of these two diseases mainly relies on manual identificatio...

Hybridization of the swarming and interior point algorithms to solve the Rabinovich-Fabrikant system.

Scientific reports
In this study, a trustworthy swarming computing procedure is demonstrated for solving the nonlinear dynamics of the Rabinovich-Fabrikant system. The nonlinear system's dynamic depends upon the three differential equations. The computational stochasti...