fig6

Computer vision for efficient object detection and segmentation in molecular image analysis

Figure 6. Performance of the incremental learning framework on the sample molecules across multiple metal substrates. (A) Visualization of molecular detection results for 4,4’-di(pyridin-4-yl)-1,1’-biphenyl in STM images acquired from Au(111), Ag(111), and Cu(111) surfaces. All STM images span 20 nm × 20 nm. Bounding boxes highlight the successfully identified molecules. In the model visualization, yellow and orange represent gold (Au) and copper (Cu) atoms, respectively; (B) Quantitative performance comparison across substrates using mAP@0.5, showing the model’s ability to maintain high detection accuracy (0.81, 0.95, and 0.99) under varying imaging conditions. STM: Scanning tunneling microscopy.

Journal of Materials Informatics
ISSN 2770-372X (Online)
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