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- Title
OPTIMIZING VEHICULAR NETWORK MANAGEMENT USING CONVOLUTIONAL NEURAL NETWORKS.
- Authors
Maurya, Mahesh; Varun, T.; latha, K. Sree; Kumar, Atul
- Abstract
CNN have been utilized in many domains and have revolutionized the field of computer vision, natural language processing and vehicular network management. CNNs are loaded with a number of advantages over the current methods of controlling vehicular networks. For instance, they can effectively handle the dynamic behavior of vehicular network due to their ability to learn recognition patterns. Additionally, CNNs are equipped with the capability to perform feature extraction along with its learning and integrating abilities, which can be highly advantageous for vehicular network management. Furthermore, they enable for parametric optimization thus increasing the speed of convergence with low-cost computational resources. Thus, CNNs are a promising approach for highly reliable communication and control of vehicular networks.
- Subjects
CABLE News Network; CONVOLUTIONAL neural networks; NATURAL language processing; COMPUTER vision; FEATURE extraction; VISUAL fields
- Publication
ICTACT Journal on Communication Technology, 2023, Vol 14, Issue 2, p2913
- ISSN
0976-0091
- Publication type
Article
- DOI
10.21917/ijct.2023.0433