Electronic components detection and recognition using deep learning for learning purpose

• Main Authors: Wan Nur Azhani, Wan Samsudin, Wai Fook, Wan, Mohd Zamri, Ibrahim, Kamarul Hawari, Ghazali, Ahmad Afif, Mohd Faudzi, Rohana, Abdul Karim
• Format: Conference or Workshop Item
• Language: English
• Published: 2021
• Subjects: T Technology (General); TA Engineering (General). Civil engineering (General); TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/34608/1/Electronic%20components%20detection%20and%20recognition%20using%20deep%20learning%20for%20learning%20purpose.CITREX2021..pdf; http://umpir.ump.edu.my/id/eprint/34608/

To assist user in detecting and recognizing accurately the electronic components using deep learning approach. It is important to choose the correct electronic components to avoid circuit failure and accident occurred. An accurate detection system based on Single Shot Detector (SSD) framework integrating with the android application is presented to help users, especially students. This application is well developed for the learning purpose.