Datasets

Vision-language pipeline extracting chemical reaction data from PDF figures and tables into structured knowledge graphs …

Weakly supervised OCSR framework combining object detection and graph construction to recognize chemical structures from …

A deep learning method using EfficientNet and Transformer to convert hand-drawn chemical structures into SMILES codes, …

Open-source OCSR platform combining Mask R-CNN segmentation and Transformer recognition, trained on 450M+ synthetic …

A graph-based deep learning approach for optical chemical structure recognition that outperforms image captioning …

OCSU task for translating molecular images into multi-level descriptions. Introduces Vis-CheBI20 dataset and …

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

Deep learning OCSR tool using YOLOv5 and MobileNetV2 to extract machine-readable molecular structures from scientific …

Deep learning model using Swin Transformer and Focal Loss for OCSR, achieving 98.58% accuracy on synthetic benchmarks.

An end-to-end deep learning approach using U-Net and CNN-LSTM to segment and predict chemical structures from document …

A micro-review of Optical Chemical Structure Recognition (OCSR), covering rule-based systems to modern deep learning …

MolParser-7M is the largest OCSR dataset with 7.7M image-text pairs of molecules and E-SMILES, including 400k real-world …