دورية أكاديمية
Detection of traffic accidents using artificial intelligence
| العنوان: | Detection of traffic accidents using artificial intelligence |
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| المؤلفون: | Jesus Gerardo Ávila Sánchez, Francisco Eneldo López Monteagudo, Francisco Javier Martinez Ruiz, Leticia del Carmen Ríos Rodríguez |
| المصدر: | ITEGAM-JETIA, Vol 10, Iss 46 (2024) |
| بيانات النشر: | Institute of Technology and Education Galileo da Amazônia, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Technology LCC:Technology (General) LCC:Science (General) |
| مصطلحات موضوعية: | Technology, Technology (General), T1-995, Science (General), Q1-390 |
| الوصف: | This article analyzes different architectures with which a neural network can be developed using computer vision with the objective of detecting traffic accidents. For the development of the software, the Java Script programming language was used, reaching the conclusion that the best architecture to use is a Convolutional Neural Network since it has the capabilities of detecting features within the images. At the same time, a database was developed with the necessary characteristics for the functioning of the neural network. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2447-0228 |
| Relation: | https://itegam-jetia.org/journal/index.php/jetia/article/view/1109; https://doaj.org/toc/2447-0228 |
| DOI: | 10.5935/jetia.v10i46.1109 |
| URL الوصول: | https://doaj.org/article/718e769849c3473aa683f6450024b43a |
| رقم الأكسشن: | edsdoj.718e769849c3473aa683f6450024b43a |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 24470228 |
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| DOI: | 10.5935/jetia.v10i46.1109 |