Transfer Learning for Mosquito Classification Using VGG16-Reference-Cited by-同舟云学术

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Transfer Learning for Mosquito Classification Using VGG16

Published:2023 Issue: Volume: Page:471-484
ISSN:2731-7870
Container-title:Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)
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Author:

Siddiqui Ayesha Anam,Kayte Charansing

Publisher

Atlantis Press International BV

Reference36 articles.

1. (K., 2019) K., D. J. (2019). Image Classification and Object Detection. SCIENCE INSIGHTS, 85–100.

2. (Mosquito-Borne Diseases. , 2014) Mosquito-Borne Diseases. . World Health Organization

3. Mosquito-borne diseases information from WHO. [On-line]. Available: http://www.who.int/neglected_diseases/vector_ecology/mosquito-borne-diseases/en/

4. Andreas Geiger, P. L. (2013). Vision meets robotics International Journal of Robotics Research (IJRR),.

5. . Zhou DX. Theory of deep convolutional neural networks: downsampling. Neural Netw. 2020;124:319–27.

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. 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

2. Application of computer vision and deep learning models to automatically classify medically important mosquitoes in North Borneo, Malaysia;Bulletin of Entomological Research;2024-04

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