
ChemPix: Hand-Drawn Hydrocarbon Recognition
Deep learning framework using CNN-LSTM image captioning to convert hand-drawn hydrocarbon structures into SMILES strings …

Deep learning framework using CNN-LSTM image captioning to convert hand-drawn hydrocarbon structures into SMILES strings …

Transformer-based approach for Optical Chemical Structure Recognition converting chemical images to SELFIES strings with …

Vision Transformer encoder with Transformer decoder for molecular image-to-InChI translation, achieving state-of-the-art …

An end-to-end framework (RCGD) and unambiguous markup language (SSML) for recognizing complex handwritten chemical …

A Transformer-based model (ICMDT) for converting chemical structure images into InChI text strings using a novel Deep …

A deep learning model that converts molecular images directly into graph structures, enabling recognition of abbreviated …
Transformer-based OCSR using a novel synthetic data generation pipeline for robust molecular image interpretation across …
Encoder-decoder model using pre-trained ResNet and attention-based LSTM to translate molecular images into SMILES, …
Deep learning OCSR tool using YOLOv5 and MobileNetV2 to extract machine-readable molecular structures from scientific …
Patch-based CNN method for detecting Markush structures in chemical images, addressing low signal-to-noise ratios in …
Systematization of OCSR evolution from rule-based systems to deep learning, highlighting the paradigm shift to image …
Ablation study comparing SMILES, DeepSMILES, SELFIES, and InChI for OCSR. SMILES achieves highest accuracy; SELFIES …