Handwritten Chemical Ring Recognition with NNs
A two-phase neural network approach for recognizing handwritten heterocyclic chemical rings with ~94% accuracy.
A two-phase neural network approach for recognizing handwritten heterocyclic chemical rings with ~94% accuracy.
A hybrid SVM and elastic matching approach for recognizing handwritten chemical symbols drawn on touch devices, …
Online recognition of handwritten chemical symbols using Hidden Markov Models with 11-dimensional local features, …

Two-stage CNN approach for converting molecular images to SMILES using CDDD embeddings and extensive data augmentation.
Two-level algorithm for recognizing on-line handwritten chemical expressions using structural analysis, ANNs, and string …
A hierarchical grammar-based approach for recognizing and analyzing online handwritten chemical formulas in mobile …
A two-level recognition algorithm for on-line handwritten chemical expressions using structural and syntactic features.
Comprehensive review and benchmarking of 30 years of Optical Chemical Structure Recognition (OCSR) methods and tools.
A dual-stage classifier combining SVM and HMM to recognize online handwritten chemical symbols, introducing a reordering …
A 2009 unified framework for inorganic/organic chemical handwriting recognition using graph search and statistical …
A hybrid system combining pattern recognition and rule-based expert systems to reconstruct chemical structures from …
ChemReader OCR software evaluation on TREC 2011 Chemical IR campaign achieving 93% accuracy on image-to-structure task.