{"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/learning-a-neural-network-based","title":"Learning a Neural-network-based Representation for Open Set Recognition","arxiv_id":"1802.04365","date":"2018-02-12","proceeding":null,"authors":["Mehadi Hassen","Philip K. Chan"],"abstract":"Open set recognition problems exist in many domains. For example in security,\nnew malware classes emerge regularly; therefore malware classification systems\nneed to identify instances from unknown classes in addition to discriminating\nbetween known classes. In this paper we present a neural network based\nrepresentation for addressing the open set recognition problem. In this\nrepresentation instances from the same class are close to each other while\ninstances from different classes are further apart, resulting in statistically\nsignificant improvement when compared to other approaches on three datasets\nfrom two different domains.","url_abs":"http://arxiv.org/abs/1802.04365v1","url_pdf":"http://arxiv.org/pdf/1802.04365v1.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":"learning-a-neural-network-based","repo_url":"https://github.com/Andrewwango/open-set-classif","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"learning-a-neural-network-based","repo_url":"https://github.com/Andrewwango/open-set-resnet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"learning-a-neural-network-based","repo_url":"https://github.com/shrtCKT/opennet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"malware-classification","task_name":"Malware Classification"},{"task_slug":"open-set-learning","task_name":"Open Set Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1802.04365","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}