Waste classification using support vector machine with SIFT-PCA feature extraction

• Main Authors: Puspaningrum, Adita Putri, Endah, Sukmawati Nur, Sasongko, Priyo Sidik, Kusumaningrum, Retno, ., Khadijah, ., Rismiyati, Ernawan, Ferda
• Format: Conference or Workshop Item
• Language: English
• Published: IEEE 2020
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://umpir.ump.edu.my/id/eprint/30353/1/Waste%20classification%20using%20support%20vector1.pdf; http://umpir.ump.edu.my/id/eprint/30353/; https://doi.org/10.1109/ICICoS51170.2020.9298982; https://doi.org/10.1109/ICICoS51170.2020.9298982

Population growth and changes in public consumption patterns cause increases in the volume, types and characteristics of the waste. This increase requires waste management effort. One of the efforts that can be performed is by separating waste into several types. Upon waste separation, the waste can...