Titlebook: Artificial Intelligence and Smart Vehicles; First International Mehdi Ghatee,S. Mehdi Hashemi Conference proceedings 2023 The Editor(s) (i

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書(shū)目名稱Artificial Intelligence and Smart Vehicles被引頻次




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書(shū)目名稱Artificial Intelligence and Smart Vehicles讀者反饋




書(shū)目名稱Artificial Intelligence and Smart Vehicles讀者反饋學(xué)科排名

敲竹杠

Personal Privacy and Information Managementur results demonstrate the potential of fractal theory and deep learning techniques for developing accurate and effective spatiotemporal prediction models, which can be utilized to identify areas and time periods of heightened risk and inform targeted intervention and prevention efforts.

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,Driver Identification by?an?Ensemble of?CNNs Obtained from?Majority-Voting Model Selection,ates that model selection using a majority vote significantly improves the accuracy of the model. Finally, the performance of this research in terms of the accuracy, precision, recall, and f1-measure are 93.22%, 95.61%, 93.22%, and 92.80% respectively when the input length is 5?min.

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Resection

1865-0929 023, held in Tehran, Iran,?during?May 24-25, 2023..The 14 full papers included in this book were carefully reviewed and?selected from?93?submissions. They were organized in topical sections as follows: machine learning, data mining, machine vision, image processing, signal analysis, decision support

講個(gè)故事逗他

engrossed

Generating Control Command for an Autonomous Vehicle Based on Environmental Information,utonomous vehicles and perform about 60% better than the networks designed from 2017 to 2021. In addition, the problem of overfitting in previous networks has mainly been addressed with the help of the new network architecture and different data preprocessing.

NATAL

Personal Privacy and Information Managementn accuracy compared to the YOLOv5 algorithms. Results show that the YOLOv81 model has the highest precision value, the YOLOv8x has the highest recall value, and the YOLOv8m and YOLOv8x have the highest mAP@50 value. Also, the mAP@50–90 values of these models are approximately equal and are the highest among other models.

粘連

Deep Learning-Based Concrete Crack Detection Using YOLO Architecture,n accuracy compared to the YOLOv5 algorithms. Results show that the YOLOv81 model has the highest precision value, the YOLOv8x has the highest recall value, and the YOLOv8m and YOLOv8x have the highest mAP@50 value. Also, the mAP@50–90 values of these models are approximately equal and are the highest among other models.

興奮過(guò)度

Conference proceedings 2023organized in topical sections as follows: machine learning, data mining, machine vision, image processing, signal analysis, decision support systems, expert systems, and their applications in smart vehicles..