Convolutional neural network-based real-time mosquito genus identification using wingbeat frequency: A binary and multiclass classification approach-Reference-Cited by-同舟云学术

Convolutional neural network-based real-time mosquito genus identification using wingbeat frequency: A binary and multiclass classification approach

Published:2024-05 Issue: Volume:80 Page:102495
ISSN:1574-9541
Container-title:Ecological Informatics
language:en
Short-container-title:Ecological Informatics

Author:

Joelianto Endra,Mandasari Miranti Indar,Marpaung Daniel Beltsazar,Hafizhan Naufal Dzaki,Heryono Teddy,Prasetyo Maria Ekawati,Dani ,Tjahjani Susy,Anggraeni Tjandra,Ahmad Intan

Funder

Ministry of Finance of the Republic of Indonesia

Publisher

Elsevier BV

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1. Monitoring Mosquito Abundance: Comparing an Optical Sensor with a Trapping Method;Insects;2024-08-01

2. Hybrid Machine Learning Approach for Mosquito Species Classification Using Wingbeat Analysis;International Journal of Scientific Research in Computer Science, Engineering and Information Technology;2024-05-10

3. Application of machine learning in automatic image identification of insects - a review;Ecological Informatics;2024-05