%0 Journal Article
	%A Micheal Olaolu Arowolo and  Muhammad Azam and  Fei He and  Mihail Popescu and  Dong Xu
	%D 2023
	%J International Journal of Biotechnology and Bioengineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 202, 2023
	%T Annotations of Gene Pathways Images in Biomedical Publications Using Siamese Network
	%U https://publications.waset.org/pdf/10013264
	%V 202
	%X As the quantity of biological articles rises, so does the number of biological route figures. Each route figure shows gene names and relationships. Manually annotating pathway diagrams is time-consuming. Advanced image understanding models could speed up curation, but they must be more precise. There is rich information in biological pathway figures. The first step to performing image understanding of these figures is to recognize gene names automatically. Classical optical character recognition methods have been employed for gene name recognition, but they are not optimized for literature mining data. This study devised a method to recognize an image bounding box of gene name as a photo using deep Siamese neural network models to outperform the existing methods using ResNet, DenseNet and Inception architectures, the results obtained about 84% accuracy. 
	%P 221 - 225