VGU RESEARCH REPOSITORY
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https://epub.vgu.edu.vn/handle/dlibvgu/1999| Title: | Deep learning-based mosquito species identification using convolutional neural networks | Authors: | Nguyen Ha Bao Ngan | Keywords: | Deep learning;Image classification;Convolution neuron network;Mosquito identification | Issue Date: | 2024 | Abstract: | This thesis explored the ability of pre-trained CNN models (VGG-16, ResNet50, Xception) to classify mosquito species based on images of their bodies and wings. The research tested these models on separate datasets of body and wing images. Xception stood out with impressive classification accuracy, achieving the highest test set scores: 95.05% for body images and 93.42% for wing images. These results suggest that Xception could be a powerful tool for accurate mosquito identification based on images. This thesis highlights the potential of Xception for practical mosquito monitoring systems. With further development, its high accuracy could make it an asset in controlling mosquito populations and preventing diseases they transmit |
URI(1): | https://epub.vgu.edu.vn/handle/dlibvgu/1999 | Rights: | Attribution-NonCommercial 4.0 International |
| Appears in Collections: | Business Information Systems (BIS) |
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| Deep learning-based mosquito species identification using convolutional neural networks.pdf | 3.54 MB | Adobe PDF |
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