Real-time chatter detection is crucial for the milling process to maintain the workpiece surface quality and minimize the generation of defective parts. In this study, we propose a new methodology based on the measurement of machine head stock struct...
This paper presents an algorithm for infrared and visible image fusion using significance detection and Convolutional Neural Networks with the aim of integrating discriminatory features and improving the overall quality of visual perception. Firstly,...
The appearance characteristics of ceramic color are an important factor in determining the user's aesthetic perception of the product. Given the problem that ceramic color varies and the user's visual sensory evaluation of color is highly subjective ...
Automatic and accurate optical coherence tomography (OCT) image classification is of great significance to computer-assisted diagnosis of retinal disease. In this study, we propose a hybrid ConvNet-Transformer network (HCTNet) and verify the feasibil...
Computational intelligence and neuroscience
Jul 20, 2022
Chronic diseases are the most severe health concern today, and heart disease is one of them. Coronary artery disease (CAD) affects blood flow to the heart, and it is the most common type of heart disease which causes a heart attack. High blood pressu...
Computational intelligence and neuroscience
Jul 20, 2022
The development in technology has resulted in the utilization of artificial intelligence systems in various fields. In this research, we are going to study cultural and creative product design and image recognition based on a convolutional neural net...
Computational intelligence and neuroscience
Jul 20, 2022
The intelligent tracking and detection of athletes' actions and the improvement of action standardization are of great practical significance to reducing the injury caused by sports in the sports industry. For the problems of nonstandard movement and...
Morphological and diagnostic evaluation of pediatric musculoskeletal system is crucial in clinical practice. However, most segmentation models do not perform well on scarce pediatric imaging data. We propose a new pre-trained regularized convolutiona...
Neural networks : the official journal of the International Neural Network Society
Jul 19, 2022
In this paper, we formulate a mixed-integer problem for sparse signal reconstruction and reformulate it as a global optimization problem with a surrogate objective function subject to underdetermined linear equations. We propose a sparse signal recon...
OBJECTIVE: Convolutional neural networks (CNNs) are being increasingly used in the medical field, especially for image recognition in high-resolution, large-volume data sets. The study represents the current state of research on the application of CN...
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