Classification of plastic materials based on spectroscopic data is a very crucial task in a variety of applications, including automated recycling, environmental monitoring, quality control in manufacturing, quality control of products, and analysis ...
Human swimming posture recognition is a key technology to improve training effect and reduce sports injury by analyzing and recognizing swimmer's movement posture. However, the existing technical means cannot accomplish the accurate recognition of hu...
Surface defect detection of organic jujubes is critical for quality assessment. However, conventional machine vision lacks adaptability to polymorphic defects, while deep learning methods face a trade-off-deep architectures are computationally intens...
Epilepsy affects around 50 million people globally, causing significant burdens. While many methods predict seizures, current models struggle with handling spatiotemporal features and balancing accuracy with computational efficiency.This paper introd...
This paper addresses the challenges of dynamic environments and multimodal data fusion in multimodal transport path optimization for smart ports by proposing a GL-SSL Model that integrates Graph Neural Networks (GCN), Long Short-Term Memory (LSTM), a...
In this study, we developed an image-recognition-based deep-learning method for accurately predicting the DSSP (define secondary structures of proteins) parameters from a circular dichroism (CD) spectrum. Focusing on the inherently high image-recogni...
In recent years, progress in artificial intelligence, particularly in the realm of deep learning, has resulted in substantial enhancements in the diagnosis of various medical conditions. This study introduces a framework that leverages multiple light...
Hair dyeing is a widespread practice with potential forensic value in individual identification, yet most analytical approaches are destructive, time-intensive, or lack sensitivity for trace residues. Surface-enhanced Raman spectroscopy (SERS) offers...
Early diagnosis and personalized intervention for Autism Spectrum Disorder (ASD) in children can potentially improve developmental outcomes, though current methods often lack scalability and adaptability. This study introduces an integrated system co...
The classification of malignant versus benign microcalcifications in mammograms remains a critical yet challenging task in breast cancer screening. Deep learning models, particularly convolutional neural networks, have demonstrated promising results;...
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