AIMC Topic: Convolutional Neural Networks

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Dose stratification-based convolutional neural networks for dose distribution prediction in radiotherapy.

Biomedical physics & engineering express
The fidelity of dose distribution prediction is paramount for radiotherapy planning. While existing deep learning-based methods have obtained noteworthy performance, most of them pursue the accurate prediction of global dose distribution but neglect ...

Wearable sensing for badminton stroke recognition with one-dimensional convolutional neural network.

Scientific reports
Motivated by the need to improve the performance of badminton players, various motion monitoring systems have been developed to assist coaches in badminton technique instruction. While traditional video or optical methods are limited to fixed scenari...

Using convolutional neural networks with late fusion to predict heart disease.

Scientific reports
Cardiovascular diseases are responsible for one-third of all deaths that occur globally. Machine learning and data mining have made it easier and quicker for physicians to diagnose or identify patients. This article presents a novel late fusion metho...

Explainable convolutional neural network architectures for high-performance taxonomic classification of gasteroid macrofungi.

Scientific reports
Gasteroid fungi represent a morphologically diverse and taxonomically challenging group due to their convergent evolution and closed fruiting bodies. This study presents a novel deep learning-based framework for the classification of six macrofungi s...

Enhancing museum collection images with fuzzy set guided convolutional neural network: A novel approach leveraging fuzzy set theory.

PloS one
Museum collection images are invaluable for preserving cultural heritage and studying history. However, these images often lack quality and clarity. This study introduces a novel museum collection image enhancement technique based on fuzzy set theory...

Recognition method of bridge apparent defects based on image processing and improved convolutional neural networks.

PloS one
As an important transportation hub, the detection of appearance defects in bridges has been characterized by low accuracy and low efficiency. To address this problem, the study proposes a bridge appearance defect recognition model based on image proc...

Emergent neuronal mechanisms mediating covert attention in convolutional neural networks.

Proceedings of the National Academy of Sciences of the United States of America
Covert visual attention allows the brain to select different regions of the visual world without eye movements. Predictive cues of a target location orient covert attention and improve perceptual performance. In most computational models, researchers...

ResNet-EfficientNet powered framework for high-precision cough-based classification of infectious diseases.

Scientific reports
COVID-19 is a extremely contagious disease triggered by the SARS-CoV-2 virus which mostly affects the human breathing system. Furthermore, the COVID-19 was emerged in late 2019 and escalated rapidly into a global pandemic which impacted health and ec...

An improved facial emotion recognition system using convolutional neural network for the optimization of human robot interaction.

Scientific reports
Artificial intelligence (AI) has been effectively augmenting the features of robotics applications, including surveillance, medical support, aid services for the elderly or disabled, and many more uses. Most robotics applications need a variety of hu...

Classification of cardiac electrical signals between patients with myocardial infarction and healthy controls by using time-frequency features and 3D convolutional neural networks.

Biomedical physics & engineering express
Electrocardiogram (ECG) signal classification plays an important role in myocardial infarction (MI) detection and screening. Despite that much progress has been made, the interpretation of ECG signals is still extremely time-consuming, and heavily re...