AIMC Topic: Neural Networks, Computer

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A meta-analysis on the effectiveness of anthropomorphism in human-robot interaction.

Science robotics
The application of anthropomorphic design features is widely assumed to facilitate human-robot interaction (HRI). However, a considerable number of study results point in the opposite direction. There is currently no comprehensive common ground on th...

Research on RNA secondary structure predicting via bidirectional recurrent neural network.

BMC bioinformatics
BACKGROUND: RNA secondary structure prediction is an important research content in the field of biological information. Predicting RNA secondary structure with pseudoknots has been proved to be an NP-hard problem. Traditional machine learning methods...

Application of CNN Algorithm Based on Chaotic Recursive Diagonal Model in Medical Image Processing.

Computational intelligence and neuroscience
With the gradual improvement of people's living standards, the production and drinking of all kinds of food is increasing. People's disease rate has increased compared with before, which leads to the increasing number of medical image processing. Tra...

AAN-Face: Attention Augmented Networks for Face Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Convolutional neural networks are capable of extracting powerful representations for face recognition. However, they tend to suffer from poor generalization due to imbalanced data distributions where a small number of classes are over-represented (e....

Neural network surgery: Combining training with topology optimization.

Neural networks : the official journal of the International Neural Network Society
With ever increasing computational capacities, neural networks become more and more proficient at solving complex tasks. However, picking a sufficiently good network topology usually relies on expert human knowledge. Neural architecture search aims t...

Physics-incorporated convolutional recurrent neural networks for source identification and forecasting of dynamical systems.

Neural networks : the official journal of the International Neural Network Society
Spatio-temporal dynamics of physical processes are generally modeled using partial differential equations (PDEs). Though the core dynamics follows some principles of physics, real-world physical processes are often driven by unknown external sources....

Bipartite synchronization of signed networks via aperiodically intermittent control based on discrete-time state observations.

Neural networks : the official journal of the International Neural Network Society
In this paper, bipartite synchronization of signed networks with stochastic disturbances via aperiodically intermittent control is investigated. The aperiodically intermittent control presented is based on discrete-time state observations rather than...

Artificial neural network for the prediction model of glomerular filtration rate to estimate the normal or abnormal stages of kidney using gamma camera.

Annals of nuclear medicine
OBJECTIVE: Chronic kidney disease (CKD) is evaluated based on glomerular filtration rate (GFR) using a gamma camera in the nuclear medicine center or hospital in a routine procedure, but the gamma camera does not provide the accurate stages of the di...

Retention time prediction in hydrophilic interaction liquid chromatography with graph neural network and transfer learning.

Journal of chromatography. A
The combination of retention time (RT), accurate mass and tandem mass spectra can improve the structural annotation in untargeted metabolomics. However, the incorporation of RT for metabolite identification has received less attention because of the ...

Colorectal Polyp Image Detection and Classification through Grayscale Images and Deep Learning.

Sensors (Basel, Switzerland)
Colonoscopy screening and colonoscopic polypectomy can decrease the incidence and mortality rate of colorectal cancer (CRC). The adenoma detection rate and accuracy of diagnosis of colorectal polyp which vary in different experienced endoscopists hav...