{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/dynamic-zoom-in-detection-of-exfoliated-two","title":"Dynamic zoom-in detection of exfoliated two-dimensional crystals using deep reinforcement learning","arxiv_id":"2209.04467","date":"2022-09-09","proceeding":null,"authors":["Stephan Kim"],"abstract":"Owing to their tunability and versatility, the two-dimensional materials are an excellent platform to conduct a variety of experiments. However, laborious device fabrication procedures remain as a major experimental challenge. One bottleneck is searching small target crystals from a large number of exfoliated crystals that greatly vary in shapes and sizes. We present a method, based on a combination of deep reinforcement learning and object detection, to accurately and efficiently discover target crystals from a high resolution image containing many microflakes. The proposed method dynamically zooms in to the region of interest and inspects it with a fine detector. Our method can be customized for searching various types of crystals with a modest computation power. We show that our method outperformed a simple baseline in detection tasks. Finally, we analyze the efficiency of the deep reinforcement learning agent in searching crystals. Codes are available at \\url{https://github.com/stephandkim/detect_crystals}.","url_abs":"https://arxiv.org/abs/2209.04467v2","url_pdf":"https://arxiv.org/pdf/2209.04467v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"dynamic-zoom-in-detection-of-exfoliated-two","repo_url":"https://github.com/stephandkim/detect_crystals","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}