Comprehensive evaluation of 8 optical chemical structure recognition tools using a newly curated dataset of 2,702 patent images. Proposes ChemIC, a ResNet-50 classifier to route images to specialized tools based on content type, demonstrating that no single tool excels at all tasks.
This systematization paper traces the history of OCSR, comparing early rule-based systems like OSRA with modern deep learning approaches like DECIMER. It highlights the shift from image classification to image captioning and identifies critical gaps in dataset standardization and evaluation metrics.
This paper reviews three decades of OCSR development, transitioning from rule-based heuristics to early deep learning approaches. It includes a benchmark study comparing the performance of three open-source tools (OSRA, Imago, MolVec) on four diverse datasets.
A resource paper detailing the CLEF-IP 2012 benchmarking lab. It introduces specific IR tasks for patent processing along with ground-truth datasets.
This resource paper details the third TREC Chemical IR campaign, introducing a novel Image-to-Structure task and analyzing 36 runs from 9 groups to benchmark chemical information retrieval.
A comprehensive categorization of OCSR methods, organizing techniques by their fundamental approach: deep learning, traditional ML, and rule-based systems.
Personal working taxonomy for categorizing papers as Method, Theory, Resource, Systematization, Position, Discovery, or Application contributions using a superposition model.