mlsanityData to 14 Oct 2026

MatGD: Materials Graph Digitizer

arXiv 2311.12806 ↗First posted 19 Sep 2023cs.CV cs.DL cs.IRcited by 4

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Abstract (arXiv)

We have developed MatGD (Material Graph Digitizer), which is a tool for digitizing a data line from scientific graphs. The algorithm behind the tool consists of four steps: (1) identifying graphs within subfigures, (2) separating axes and data sections, (3) discerning the data lines by eliminating irrelevant graph objects and matching with the legend, and (4) data extraction and saving. From the 62,534 papers in the areas of batteries, catalysis, and MOFs, 501,045 figures were mined. Remarkably, our tool showcased performance with over 99% accuracy in legend marker and text detection. Moreover, its capability for data line separation stood at 66%, which is much higher compared to other existing figure mining tools. We believe that this tool will be integral to collecting both past and future data from publications, and these data can be used to train various machine learning models that can enhance material predictions and new materials discovery.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 4 of its 26 references that are in the map. First posted on arXiv 19 Sep 2023.

Builds on

4 of 26 references.

References · 4

  1. 2021MatSciBERT: A Materials Domain Language Model for Text Mining and Information Extractioncited by 83
  2. 2021Using Machine Learning and Data Mining to Leverage Community Knowledge for the Engineering of Stable Metal-Organic Frameworkscited by 20
  3. 2021Looking Through Glass: Knowledge Discovery from Materials Science Literature using Natural Language Processingcited by 16
  4. 2019Aerial Images Processing for Car Detection using Convolutional Neural Networks: Comparison between Faster R-CNN and YoloV3cited by 5

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 0; 2026: 2.

4 papers.

  1. 2024Machine Learning Based Prediction of Proton Conductivity in Metal-Organic Frameworkscited by 2
  2. 2024Text-to-Battery Recipe: A language modeling-based protocol for automatic battery recipe extraction and retrievalcited by 2
  3. 2026Beyond Text and Tables: Vision-Language Model Integration in ComProScanner for Extracting Materials Data from Scientific Figures with High Accuracycited by 1
  4. 2026Multimodal Transformer for Sample-Aware Prediction of Metal-Organic Framework Propertiescited by 0