Molecular-InChI: Automated Recognition of Optical Chemical Structure

dc.contributor.authorKumar, N.
dc.contributor.authorRashmi, M.
dc.contributor.authorRamu, S.
dc.contributor.authorReddy Guddeti, R.M.
dc.date.accessioned2026-02-06T06:35:28Z
dc.date.issued2022
dc.description.abstractWith the advent of a new era dominated by digital media and publications in recent years, the importance of striking a balance between traditional and new modes of operation has become increasingly apparent. It has been standard practice in the field of chemistry for decades to express chemical compounds using their structural forms, referred to as the Skeletal formula. In this research, we tried to interpret these old chemical structure images, extracted from old literature, to transform pictures back to the underlying chemical structure labeled as InChI text using a huge set of synthetic image data produced by Bristol-Myers Squibb. In this paper, we propose an improved synthetic data and an Encoder-Decoder-based deep learning-based model to automatically represent these molecular images into their underlying InChI representation. © 2022 IEEE.
dc.identifier.citation2022 IEEE Region 10 Symposium, TENSYMP 2022, 2022, Vol., , p. -
dc.identifier.urihttps://doi.org/10.1109/TENSYMP54529.2022.9864516
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/29880
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectChemical Compound
dc.subjectEfficientNetB0
dc.subjectImage processing
dc.subjectInCh
dc.subjectI LSTM
dc.subjectMolecular Representation
dc.titleMolecular-InChI: Automated Recognition of Optical Chemical Structure

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