
Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)
Published: Dec. 4, 2024
Language: Английский
Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)
Published: Dec. 4, 2024
Language: Английский
Heliyon, Journal Year: 2025, Volume and Issue: 11(2), P. e41767 - e41767
Published: Jan. 1, 2025
Language: Английский
Citations
3Biomedical Signal Processing and Control, Journal Year: 2025, Volume and Issue: 105, P. 107610 - 107610
Published: Feb. 4, 2025
Language: Английский
Citations
1Multimedia Tools and Applications, Journal Year: 2024, Volume and Issue: unknown
Published: June 3, 2024
Language: Английский
Citations
4Communications in computer and information science, Journal Year: 2025, Volume and Issue: unknown, P. 48 - 57
Published: Jan. 1, 2025
Language: Английский
Citations
0Signal Image and Video Processing, Journal Year: 2025, Volume and Issue: 19(4)
Published: Feb. 14, 2025
Language: Английский
Citations
0Applied Mathematics and Nonlinear Sciences, Journal Year: 2025, Volume and Issue: 10(1)
Published: Jan. 1, 2025
Abstract Patent data possesses characteristics such as a large amount of relevant data, volume and an application management process that is difficult to control. The protection patent intellectual property rights will be impacted by these features. In order solve the above problems, this paper, in context artificial intelligence technology, takes clothing appearance research object, adopts normalization method mine extract features, uses View-GCN graph convolution module learn features view, after builds DP-MVGCN model based on neural network for classification property. Finally, applied build effective discuss impact cultural industry. results show feature extraction rate >95% when number training times reaches 70. At k=3.0, has highest score result test set 4 evaluation indexes, good accuracy. Starting from 2020, measured values three indices judicial protection, administrative social have increased sharply over time. By 2023 indexes pathways 1.27 times, 1.29 1.26 respectively compared 2020. It clear reasonable patents can significantly improve patented knowledge, also enhance degree industry agglomeration promote self-production subcultural clusters.
Language: Английский
Citations
0Applied Sciences, Journal Year: 2025, Volume and Issue: 15(5), P. 2328 - 2328
Published: Feb. 21, 2025
Electroencephalography-based emotion recognition is essential for brain-computer interface combined with artificial intelligence. This paper proposes a novel algorithm human detection using hybrid paradigm of convolutional neural networks and boosting model. The proposed employs two subsets 18 14 features extracted from four sub-bands discrete wavelet transform. These are identified as the optimal most relevant, among 42 original input 8 6 productive channels dual genetic wise-subject 5-fold cross validation procedure in which first second algorithms address efficient feature subsets. estimated by differently intelligent models on set. produces an accuracy 70.43%/76.05%, precision 69.88%/74.57%, recall 98.70%/99.17%, F1 score 81.83%/85.13% valence/arousal classifications, suggest that frontal left regions cortex associate especially to emotions.
Language: Английский
Citations
0Cluster Computing, Journal Year: 2025, Volume and Issue: 28(4)
Published: Feb. 25, 2025
Language: Английский
Citations
0Information Fusion, Journal Year: 2025, Volume and Issue: unknown, P. 103229 - 103229
Published: April 1, 2025
Language: Английский
Citations
0Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)
Published: April 29, 2025
Visually impaired individuals often face various obstacles when navigating blind roads, such as road disconnections, obstructions, and more complex emergencies, which can leave them in difficult situations. Traditional early warning methods suffer from low accuracy lack real-time capabilities. Therefore, this study proposes a novel system for traffic jams on roads. By analyzing the emotional state (normal, mild anxiety, extreme anxiety) electroencephalogram (EEG) signals of visually they are trapped, determine whether distress require assistance. Additionally, considering complexity environment fact that EEG prone to external interference during acquisition, introduces an improved deep residual shrinkage network based dense blocks (DB-DRSN). DB-DRSN replaces convolutional hidden layer original module with integrates connections optimize use both shallow features. The results show achieves 96.72% recognizing difficulties faced by impaired, significantly outperforming traditional models. Compared other methods, proposed offers quicker assistance individuals. demonstrated strong performance detecting about jams, greatly enhancing safety enabling timely detection intervention.
Language: Английский
Citations
0