ArticleInsects2023
Deep Learning-Based Image Classification for Major Mosquito Species Inhabiting Korea.
Article in Insects, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
12 citing papers in PubMed, 20 citations in OpenAlex.
- A structured literature review of computer vision methods for insect identification.Journal of insect science (Online) · 2026Review
- An autonomous intelligent mosquito sentinel for field-deployed surveillance.Communications engineering · 2026Article
- Aphid-ResNetSwin: An Image Recognition Method with Improved Attention Mechanism for Graded Identification ofInsects · 2026Article
- A novel deep learning approach for mosquito species classification via a dual-head structure and calibration-aware fusion architecture.Scientific reports · 2026Article
- Article
- Hierarchical image classification using transfer learning to improve deep learning model performance for amazon parrots.Scientific reports · 2025Article
- Enhance fashion classification of mosquito vector species via self-supervised vision transformer.Scientific reports · 2024Article
- Efficient Convolutional Neural Network Model for the Taxonomy and Sex Identification of Three Phlebotomine Sandfly Species (Diptera, Psychodidae, and Phlebotominae).Animals : an open access journal from MDPI · 2024Article
- Advanced vision transformers and open-set learning for robust mosquito classification: A novel approach to entomological studies.PLoS computational biology · 2024Article
- Considerations for first field trials of low-threshold gene drive for malaria vector control.Malaria journal · 2024Review
- Automated differentiation of mixed populations of free-flying female mosquitoes under semi-field conditions.Scientific reports · 2024Article
- From beasts to bytes: Revolutionizing zoological research with artificial intelligence.Zoological research · 2023Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Mosquitoes are one of the deadliest insects, causing harm to humans worldwide. Preemptive prevention and forecasting are important to prevent mosquito-borne diseases. However, current mosquito identification is mostly conducted manually, which consumes time, wastes labor, and causes human error. In this study, we developed an automatic image analysis method to identify mosquito species using a deep learning-based object detection technique. Color and fluorescence images of live mosquitoes were acquired using a mosquito capture device and were used to develop a deep learning-based object detection model. Among the deep learning-based object identification models, the combination of a swine transformer and a faster region-convolutional neural network model demonstrated the best performance, with a 91.7% F1-score. This indicates that the proposed automatic identification method can be rapidly applied for efficient analysis of species and populations of vector-borne mosquitoes with reduced labor in the field.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.