{"total":16,"rows":[{"id":"2107.13841","title":"Addressing materials' microstructure diversity using transfer learning","created":"2021-07-29","cited_by_count":4,"area":null},{"id":"2104.11159","title":"An End-to-End Computer Vision Methodology for Quantitative Metallography","created":"2021-04-22","cited_by_count":3,"area":null},{"id":"2203.13875","title":"Semi-supervised machine learning model for analysis of nanowire morphologies from transmission electron microscopy images","created":"2022-03-25","cited_by_count":2,"area":null},{"id":"2208.04149","title":"Computer Vision Methods for the Microstructural Analysis of Materials: The State-of-the-art and Future Perspectives","created":"2022-07-29","cited_by_count":2,"area":null},{"id":"2409.13498","title":"A Deep Learning Approach for Pixel-level Material Classification via Hyperspectral Imaging","created":"2024-09-20","cited_by_count":2,"area":null},{"id":"2203.13718","title":"Digital Fingerprinting of Microstructures","created":"2022-03-25","cited_by_count":1,"area":null},{"id":"2302.08495","title":"Parameters, Properties, and Process: Conditional Neural Generation of Realistic SEM Imagery Towards ML-assisted Advanced Manufacturing","created":"2023-01-13","cited_by_count":1,"area":null},{"id":"2602.04154","title":"Context Determines Optimal Architecture in Materials Segmentation","created":"2026-02-04","cited_by_count":1,"area":null},{"id":"2305.07790","title":"Automated Grain Boundary (GB) Segmentation and Microstructural Analysis in 347H Stainless Steel Using Deep Learning and Multimodal Microscopy","created":"2023-05-12","cited_by_count":0,"area":null},{"id":"2309.00058","title":"Bellybutton: Accessible and Customizable Deep-Learning Image Segmentation","created":"2023-08-31","cited_by_count":0,"area":null},{"id":"2403.18337","title":"Macroscale fracture surface segmentation via semi-supervised learning considering the structural similarity","created":"2024-03-27","cited_by_count":0,"area":null},{"id":"2404.08017","title":"AI-Guided Feature Segmentation Techniques to Model Features from Single Crystal Diamond Growth","created":"2024-04-10","cited_by_count":0,"area":null},{"id":"2502.07107","title":"A Framework for Supervised and Unsupervised Segmentation and Classification of Materials Microstructure Images","created":"2025-02-10","cited_by_count":0,"area":null},{"id":"2602.01710","title":"Physics Informed Generative AI Enabling Labour Free Segmentation For Microscopy Analysis","created":"2026-02-02","cited_by_count":0,"area":null},{"id":"2607.28695","title":"Predicting Steel Fatigue Life from Micrographs Using Physics-Informed Deep Learning","created":"2026-07-30","cited_by_count":0,"area":null},{"id":"2610.12216","title":"Stride Independent Patching for Deep Learning","created":"2026-10-08","cited_by_count":0,"area":null}],"next_cursor":null}