Real-time detection of rare roadside obstacles using YOLOv8-n in autonomous vehicles.
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| Title: | Real-time detection of rare roadside obstacles using YOLOv8-n in autonomous vehicles. |
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| Authors: | Tanveer AB; Faculty of Computing and Informatics (FCI), Multimedia University, Cyberjaya, Malaysia.; Department of Software Engineering, National University of Technology, Islamabad, Pakistan., Kamal MA; Faculty of Computing and Informatics (FCI), Multimedia University, Cyberjaya, Malaysia.; Department of Computer Science, DHA Suffa University, Karachi, Pakistan., Alam MM; Faculty of Computing and Informatics (FCI), Multimedia University, Cyberjaya, Malaysia.; Department of Computer Science and Software Engineering, Riphah International University, Islamabad, Pakistan., Su'ud MM; Faculty of Computing and Informatics (FCI), Multimedia University, Cyberjaya, Malaysia. |
| Source: | PloS one [PLoS One] 2026 Jun 12; Vol. 21 (6), pp. e0350732. Date of Electronic Publication: 2026 Jun 12 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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