{"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/a-comparative-analysis-on-bangla-handwritten","title":"A Comparative Analysis on Bangla Handwritten Digit Recognition with Data Augmentation and Non-Augmentation Process","arxiv_id":null,"date":"2020-06-26","proceeding":"International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA) 2020 6","authors":["MD Abdullah Al Nasim","Refat E Ferdous","Mahim Anzum Haque Pantho","Atiqul Islam Chowdhury"],"abstract":"Determination of Bangla handwritten digit is a\r\nmomentous image classification task. Though object recognition\r\ntechnology is getting smarter day by day, still Bangla handwritten\r\ndigit recognition remains inconclusive. Researchers are becoming\r\nmore concerned about handwritten digit recognition for it’s\r\neducational and advantageous importance. But it is a matter\r\nof trouble that the improvement in Bangla handwritten digit\r\nrecognition is significantly less as compared to the other languages. To improve the performance of the Bangla handwritten\r\ndigit recognition system, we have designed a model, in which\r\nall basic Bangla digits have been classified. Furthermore, we\r\nhave also demonstrated Densenet121 architecture in our system.\r\nFor recognizing Bangla handwriting digits, we proposed CNN\r\n(Convolution Neural Network) model. Our system has been\r\nexperimented on the NumtaDB dataset for recognizing Bangla\r\ndigit both with augmentation and non-augmentation.","url_abs":"https://scholar.google.com/citations?view_op=view_citation&hl=en&user=zQKHA64AAAAJ&citation_for_view=zQKHA64AAAAJ:d1gkVwhDpl0C","url_pdf":"https://ieeexplore.ieee.org/abstract/document/9152905/","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":"abstracts"},"code_links":[{"paper_slug":"a-comparative-analysis-on-bangla-handwritten","repo_url":"https://github.com/nasim-aust/Bangla-Handwritten-Digit-Recognition-using-CNN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"data-augmentation","task_name":"Data Augmentation"},{"task_slug":"handwritten-digit-recognition","task_name":"Handwritten Digit Recognition"},{"task_slug":"image-classification","task_name":"Image Classification"},{"task_slug":"object-recognition","task_name":"Object Recognition"},{"task_slug":"image-classification","task_name":"image-classification"}],"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}