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CLiDE Pro: The Latest Generation of CLiDE, a Tool for Optical Chemical Structure Recognition

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Fast polygonal approximation of digitized curves
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A survey of the hough transform
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New Computer Program Reads, Interprets Chemical Structures
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Kekule: OCR-optical chemical (structure) recognition
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Chemical literature data extraction: The CLiDE Project
inferredcites →https://doi.org/10.1021/ci00067a014openalex-snapshot
Computational perception and recognition of digitized molecular structures
inferredcites →https://doi.org/10.1021/ci800067ropenalex-snapshot
Optical Structure Recognition Software To Recover Chemical Information: OSRA, An Open Source Solution
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Data Structures and Algorithms
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Automatic Recognition of Chemical Images
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Optical recognition of chemical graphics
inferredcites →https://doi.org/10.1186/1752-153x-3-4openalex-snapshot
Automated extraction of chemical structure information from digital raster images

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Accessible Chemical Structural Formulas Through Interactive Document Labeling
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Inconsistency-Driven Chemical Graph Construction in ChemInfty
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Silver threads
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Many InChIs and quite some feat
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Multi-Scale Memory-Enhanced Transformer for Optical Chemical Structure Recognition
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Chemical Data Formats, Fingerprints, and Other Molecular Descriptions for Database Analysis and Searching
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Artificial intelligence-driven patent analysis in drug discovery
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Mobile apps for chemistry in the world of drug discovery
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Text mining patents for biomedical knowledge
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A survey on automated and AI-based tools for patent retrieval with a special focus on the life sciences domain
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A Benchmark Evaluation of Chemical Structure Extraction from Patents: Insights and Challenges in Chemical Structure Recognition
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Information Retrieval and Text Mining Technologies for Chemistry
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MolScribe: Robust Molecular Structure Recognition with Image-to-Graph Generation
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ReactionDataExtractor 2.0: A Deep Learning Approach for Data Extraction from Chemical Reaction Schemes
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Tunable Machine Vision-Based Strategy for Automated Annotation of Chemical Databases
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DECIMER.ai: an open platform for automated optical chemical structure identification, segmentation and recognition in scientific publications
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Automation and machine learning augmented by large language models in a catalysis study
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MMSSC-Net: multi-stage sequence cognitive networks for drug molecule recognition
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ABC-Net: a divide-and-conquer based deep learning architecture for SMILES recognition from molecular images
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Automatic identification of relevant chemical compounds from patents
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SCRIPDB: a portal for easy access to syntheses, chemicals and reactions in patents
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Image-based automated chemical database annotation with ensemble of machine-vision classifiers
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Exposing the hidden web for chemical digital libraries
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Taking chemistry to the task
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Displaying chemical structural formulae in ePub format
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Applications of Text Detection and its Challenges
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AutoChemplete - Making Chemical Structural Formulas Accessible
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MACReD: A Multi-Agent Collaborative Reasoning Framework for Reaction Diagram Parsing
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Use of Machine Learning and Large Language Models in Chemical Information Extraction
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Interactive Quantum Chemistry Enabled by Machine Learning, Graphical Processing Units, and Cloud Computing
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ChemEx: information extraction system for chemical data curation
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Machines first, humans second: on the importance of algorithmic interpretation of open chemistry data
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A review of optical chemical structure recognition tools
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DECIMER—hand-drawn molecule images dataset
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SwinOCSR: end-to-end optical chemical structure recognition using a Swin Transformer
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Review of techniques and models used in optical chemical structure recognition in images and scanned documents
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Automated molecular structure segmentation from documents using ChemSAM
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MolNexTR: a generalized deep learning model for molecular image recognition
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Patent Retrieval
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Research on automatic recognition of hand-drawn chemical molecular structures based on deep learning
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Enhancing the Discovery of Chemistry Theses by Registering Substances and Depositing in PubChem
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MolAR: Bringing Chemical Structures to Life with Augmented Reality and Machine Learning
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Additional file 1 of Automated molecular structure segmentation from documents using ChemSAM
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Automated InChI Sequence Generation from Chemical Images with Configurable Encoder-Decoder Architecture
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