Development of a deep learning model from breeding substrate images: a novel method for estimating the abundance of house fly (Musca domestica L.) larvae.

Journal: Pest management science
Published Date:

Abstract

BACKGROUND: The application of computer vision and deep learning to pest monitoring has recently received much attention. Although several studies have demonstrated the application of object detection to the number of pests on a substrate, for house flies (Musca domestica L.), in which the larvae were aggregated and overlapped together, the object detection technique was difficult to implement. We demonstrate a novel method for estimating larval abundance by using computer vision on larval breeding substrate, in which the reflective color and topography are affected by the size of the population.

Authors

  • Song-Quan Ong
    UOW Malaysia KDU Penang University College, 32, Jalan Anson, 10400, George Town, Pulau Pinang, Malaysia. songguan26@gmail.com.
  • Hamdan Ahmad
    Vector Control Research Unit, School of Biological Sciences, Universiti Sains Malaysia, 11800, Penang, Malaysia. hamdana@usm.my.
  • Abdul Hafiz Ab Majid
    Vector Control Research Unit, School of Biological Sciences, Universiti Sains Malaysia, 11800, Penang, Malaysia.