A protocol for developing a classification system of mosquitoes using transfer learning

Pradeep Isawasan and Zetty Ilham Abdullah and Ong, Song Quan and Khairulliza Ahmad Salleh (2022) A protocol for developing a classification system of mosquitoes using transfer learning. MethodsX, 10. pp. 1-6. ISSN 2215-0161

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Abstract

Mosquito identification and classification are the most important steps in a surveillance program of mosquito-borne diseases. With conventional approach of data collection, the process of sorting and classification are laborious and time-consuming. The advancement of computer vision with transfer learning provides excellent alternative to the challenge. Transfer learning is a type of machine learning that is viable and durable in image classification with limited training images. This protocol aims to develop step-by-step procedure in developing a classification system with transfer learning algorithm for mosquito, we demonstrate the protocol to classify two species of Aedes mosquito - Aedes aegypti L. and Aedes albopitus L, but user can adopt the protocol for higher number of species classification. We demonstrated the way of start from the scratch, fine-tuning two pre-trained model performance by using different combination of hyperparameters – batch size and learning rate, and explain the terminology in the Appendix. This protocol target on the domain expert such as entomologist and public health practices to develop their own model to solve the task of mosquito/insect classification.

Item Type:	Article
Keyword:	Aedes aegypti, Aedes albopictus, Deep learning, Expert system, Mosquito automated recognition system
Subjects:	Q Science > QL Zoology > QL1-991 Zoology > QL360-599.82 Invertebrates > QL461-599.82 Insects R Medicine > RA Public aspects of medicine > RA1-1270 Public aspects of medicine > RA421-790.95 Public health. Hygiene. Preventive medicine
Department:	INSTITUTE > Institute for Tropical Biology and Conservation
Depositing User:	SITI AZIZAH BINTI IDRIS -
Date Deposited:	03 Sep 2025 10:31
Last Modified:	03 Sep 2025 10:31
URI:	https://eprints.ums.edu.my/id/eprint/45113

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