MolNexTR is a deep learning model designed to recognize molecular structures from various drawing styles prevalent in chemical literature. It combines ConvNext and Vision-Transformer to extract local and global features, predict atoms and bonds, and understand layout rules. The model incorporates advanced algorithms for data augmentation, image contamination simulation, and post-processing to enhance robustness against diverse imagery styles. MolNexTR outperforms previous models with an accuracy rate of 81-97% on test sets, marking significant progress in the field of molecular structure recognition.
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by Yufan Chen,C... a las arxiv.org 03-07-2024
https://arxiv.org/pdf/2403.03691.pdfConsultas más profundas