{"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/the-effectiveness-of-data-augmentation-in","title":"The Effectiveness of Data Augmentation in Image Classification using Deep Learning","arxiv_id":"1712.04621","date":"2017-12-13","proceeding":null,"authors":["Luis Perez","Jason Wang"],"abstract":"In this paper, we explore and compare multiple solutions to the problem of\ndata augmentation in image classification. Previous work has demonstrated the\neffectiveness of data augmentation through simple techniques, such as cropping,\nrotating, and flipping input images. We artificially constrain our access to\ndata to a small subset of the ImageNet dataset, and compare each data\naugmentation technique in turn. One of the more successful data augmentations\nstrategies is the traditional transformations mentioned above. We also\nexperiment with GANs to generate images of different styles. Finally, we\npropose a method to allow a neural net to learn augmentations that best improve\nthe classifier, which we call neural augmentation. We discuss the successes and\nshortcomings of this method on various datasets.","url_abs":"http://arxiv.org/abs/1712.04621v1","url_pdf":"http://arxiv.org/pdf/1712.04621v1.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":"abstracts"},"code_links":[{"paper_slug":"the-effectiveness-of-data-augmentation-in","repo_url":"https://github.com/kandluis/nn-data-augmentation","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"tf","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"data-augmentation","task_name":"Data Augmentation"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"image-classification","task_name":"Image Classification"},{"task_slug":"image-classification","task_name":"image-classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1712.04621","atlas_url":"https://app.syntology.ai/?focus=1712.04621","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}