{"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/convolutional-radio-modulation-recognition","title":"Convolutional Radio Modulation Recognition Networks","arxiv_id":"1602.04105","date":"2016-02-12","proceeding":null,"authors":["Timothy J. O'Shea","Johnathan Corgan","T. Charles Clancy"],"abstract":"We study the adaptation of convolutional neural networks to the complex\ntemporal radio signal domain. We compare the efficacy of radio modulation\nclassification using naively learned features against using expert features\nwhich are widely used in the field today and we show significant performance\nimprovements. We show that blind temporal learning on large and densely encoded\ntime series using deep convolutional neural networks is viable and a strong\ncandidate approach for this task especially at low signal to noise ratio.","url_abs":"http://arxiv.org/abs/1602.04105v3","url_pdf":"http://arxiv.org/pdf/1602.04105v3.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":"convolutional-radio-modulation-recognition","repo_url":"https://github.com/genesys-neu/t-prime","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"convolutional-radio-modulation-recognition","repo_url":"https://github.com/giotobar/RF-Classification","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"convolutional-radio-modulation-recognition","repo_url":"https://github.com/jamesshao8/cnn-limesdr","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"convolutional-radio-modulation-recognition","repo_url":"https://github.com/jdcneto/Modulation-Classification","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"convolutional-radio-modulation-recognition","repo_url":"https://github.com/marwan-elsafty/modulation-classification","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"convolutional-radio-modulation-recognition","repo_url":"https://github.com/mistic-lab/IPSW-RFI","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"convolutional-radio-modulation-recognition","repo_url":"https://github.com/randaller/cnn-rtlsdr","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"convolutional-radio-modulation-recognition","repo_url":"https://github.com/rowantahseen/Modulation-Classification","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"time-series-1","task_name":"Time Series"},{"task_slug":"time-series","task_name":"Time Series Analysis"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}