Deep Learning to Mosquitoes Species Pattern Recognition

Conference proceedings article

ผู้เขียน/บรรณาธิการ

กลุ่มสาขาการวิจัยเชิงกลยุทธ์

รายละเอียดสำหรับงานพิมพ์

รายชื่อผู้แต่ง: Boonprakong P., Chamnongthai K., Patchoo W., Mongkalangoon P.

ผู้เผยแพร่: Taiwan Association for Aerosol Research

ปีที่เผยแพร่ (ค.ศ.): 2021

หน้าแรก: 464

หน้าสุดท้าย: 468

จำนวนหน้า: 5

ISBN: 9781665411974

นอก: 1680-8584

eISSN: 2071-1409

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125166275&doi=10.1109%2fICSEC53205.2021.9684591&partnerID=40&md5=035b048295b28a2b78c6118ae56a7568

ภาษา: English-Great Britain (EN-GB)

ดูบนเว็บไซต์ของสำนักพิมพ์

บทคัดย่อ

The epidemic from mosquito-borne pathogens is difficult to control and monitor and is considered as a silent threat that cannot be realized. Importantly, therapeutic vaccines are developed to increase immunization to avoid the danger of life. We found these problems in daily life. Mosquitoes live with people in society and the most common species are Aedes Aegypti, Aedes Albopictus, Anopheles minimus, Culex Quinquefasciatus and Armigeres subalbatus. In general, they carry germs to people. In this paper, we are interested in classifying 5 types of mosquitoes. So, we apply LeNet 5. The results show that training network for is each species has the accuracy of 96-99%. Testing network for is each species has the accuracy of 96.25% The results are based on mosquitoes image dataset of 1, 200 images, divided as 840 training images and 120 validating images, and 240 testing images. © 2021 IEEE.

คำสำคัญ

LeNet5, Mosquitoes species