%0 Journal Article
	%A Muhammad Azam and  Micheal Olaolu Arowolo and  Fei He and  Mihail Popescu and  Dong Xu
	%D 2023
	%J International Journal of Bioengineering and Life Sciences
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 197, 2023
	%T Recognition of Gene Names from Gene Pathway Figures Using Siamese Network
	%U https://publications.waset.org/pdf/10013091
	%V 197
	%X The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than Optical Character Recognition (OCR) results.
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