Optical Chemical Structure Recognition

Comparative analysis of image-to-sequence OCSR methods across architecture, output format, training data, and compute …

A diffusion-based data augmentation pipeline (OCSAug) using DDPM and RePaint to improve optical chemical structure …

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, …

Benchmark of 8 open-access OCSR methods on 2702 manually curated patent images, with ChemIC classifier for hybrid …

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

A Transformer-based OCSR model introducing dual-path modules (CGFE and SDGLA) to improve global context awareness and …

An improved encoder-decoder model (EfficientNetV2 + Transformer) for converting hand-drawn chemical structures into …

Deep learning model using improved SwinTransformer encoder and attention-based feature fusion to convert molecular …

Multi-modal transformer combining vision, text, and layout encoding to extract complex Markush structures from patent …

A deep learning model for Optical Chemical Structure Recognition (OCSR) using SwinV2 and GPT-2 to convert molecular …

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