{"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/committees-of-deep-feedforward-networks","title":"Committees of deep feedforward networks trained with few data","arxiv_id":"1406.5947","date":"2014-06-23","proceeding":null,"authors":["Bogdan Miclut","Thomas Kaester","Thomas Martinetz","Erhardt Barth"],"abstract":"Deep convolutional neural networks are known to give good results on image\nclassification tasks. In this paper we present a method to improve the\nclassification result by combining multiple such networks in a committee. We\nadopt the STL-10 dataset which has very few training examples and show that our\nmethod can achieve results that are better than the state of the art. The\nnetworks are trained layer-wise and no backpropagation is used. We also explore\nthe effects of dataset augmentation by mirroring, rotation, and scaling.","url_abs":"http://arxiv.org/abs/1406.5947v1","url_pdf":"http://arxiv.org/pdf/1406.5947v1.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":[],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"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":[{"leaderboard":"/sota/image-classification-on-stl-10","task":"Image Classification","dataset":"STL-10","model":"DFF Committees","rank_in_archive_order":97,"of":117,"metrics":{"Percentage correct":"68"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}