Real-Time KenalKayu System with YOLOv3

• Main Authors: Rosli, N.R., Khairuddin, U., Fathi, M.F.N., Khairuddin, A.S.M., Ahmad, A.
• Format: Article
• Published: Springer Science and Business Media Deutschland GmbH 2021
• Subjects: T Technology (General)
• Online Access: http://eprints.um.edu.my/35905/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104453117&doi=10.1007%2f978-3-030-70917-4_22&partnerID=40&md5=7333c1a5daaddb082e0b698d9f3cc1af

An automated tropical wood species recognition system known as KenalKayu has been developed by the Centre for Artificial Intelligence & Robotics (CAIRO) to identify the tropical wood species. The system works very well in offline mode with an accuracy rate of up to 98. But when it comes to real-...