Molecular Image Recognition Based on EfficientNetV2 and LSTM
SU Qihong
HE Liwen
Abstract：Accurate molecular image recognition is essential for understanding the function of chemistry and its role in various biological processes,as well as for developing new drugs and treatments.In response to the low efficiency and accuracy of traditional methods for identifying molecular images,a combination of the EfficientNetV2 network and a multi-layer LSTM with a hybrid atten-tion mechanism is proposed to generate text from images and efficiently recognize molecular images.Multiple machine learning ex-periments are conducted with different encoders and decoders to obtain comparative results.The experimental results showes that compared to traditional machine learning models,this model has shorter training time and higher accuracy,achieving an accuracy of 93.1%in molecular image recognition.The combination of EfficientNetV2 and LSTM provides a promising method for molecular image recognition,simplifying the work of molecular image recognition and providing assistance for future chemical research.
Keywords：EfficientNetV2attention mechanismLSTMmolecular imageInChI
Publication Date：2025-12-20
Online Publishing Date：2026-03-09(First online date of this platform, not the publication date of the document)
Pages：5( 3519-3523 )