Real-time KenalKayu system with YOLOv3

• Main Authors: Rosli, Nenny Ruthfalydia, Khairuddin, Uswah, Nor Fathi, Muhammad Faris, Mohd. Khairuddin, Anis Salwa, Ahmad, Azlin
• Format: Conference or Workshop Item
• Published: 2021
• Subjects: T Technology (General)
• Online Access: http://eprints.utm.my/id/eprint/98060/; http://dx.doi.org/10.1007/978-3-030-70917-4_22
• Institution: Universiti Teknologi Malaysia

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...