{"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/190411093","title":"Deep Sparse Representation-based Classification","arxiv_id":"1904.11093","date":"2019-04-24","proceeding":null,"authors":["Mahdi Abavisani","Vishal M. Patel"],"abstract":"We present a transductive deep learning-based formulation for the sparse\nrepresentation-based classification (SRC) method. The proposed network consists\nof a convolutional autoencoder along with a fully-connected layer. The role of\nthe autoencoder network is to learn robust deep features for classification. On\nthe other hand, the fully-connected layer, which is placed in between the\nencoder and the decoder networks, is responsible for finding the sparse\nrepresentation. The estimated sparse codes are then used for classification.\nVarious experiments on three different datasets show that the proposed network\nleads to sparse representations that give better classification results than\nstate-of-the-art SRC methods. The source code is available at:\ngithub.com/mahdiabavisani/DSRC.","url_abs":"http://arxiv.org/abs/1904.11093v1","url_pdf":"http://arxiv.org/pdf/1904.11093v1.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":"190411093","repo_url":"https://github.com/mahdiabavisani/DSRC","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"decoder","task_name":"Decoder"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"image-classification","task_name":"Image Classification"},{"task_slug":"semi-supervised-image-classification","task_name":"Semi-Supervised Image Classification"},{"task_slug":"sparse-representation-based-classification","task_name":"Sparse Representation-based Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/sparse-representation-based-classification-on","task":"Sparse Representation-based Classification","dataset":"SVHN","model":"DSRC","rank_in_archive_order":1,"of":1,"metrics":{"Accuracy":"67.75"},"uses_additional_data":false}],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}