Insect detection and monitoring in stored grains using MFCCs and artificial neural network

• Main Authors: Santiago, Robert Martin C., Rabano, Stephenn L., Billones, Robert Kerwin D., Calilung, Edwin J., Sybingco, Edwin, Dadios, Elmer P.
• Format: text
• Published: Animo Repository 2017
• Subjects: Rice—Storage—Diseases and injuries; Acoustic emission testing; Neural networks (Computer science); Electrical and Electronics; Systems and Communications
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/1340; https://animorepository.dlsu.edu.ph/context/faculty_research/article/2339/type/native/viewcontent
• Institution: De La Salle University

The variability in grain production makes it necessary to have strategic grain storage plans in order to ensure adequate supplies at all times. However, insects in stored grain products cause infestation and contamination which reduce grain quality and quantity. In order to prevent these problems, e...