{"url":"/method/densenas-c","slug":"densenas-c","name":"DenseNAS-C","full_name":"DenseNAS-C","full_name_withheld":false,"description_markdown":"**DenseNAS-C** is a mobile convolutional neural network discovered through the [DenseNAS](https://paperswithcode.com/method/densenas) [neural architecture search](https://paperswithcode.com/method/neural-architecture-search) method. The basic building block is MBConvs, or inverted bottleneck residuals, from the [MobileNet](https://paperswithcode.com/method/mobilenetv2) architectures.","description_state":"present","introduced_year":null,"introduced_by":{"title":null,"paper":null,"first_author":null,"n_authors":0,"url_abs":null,"archive_paper_url":null},"source":{"url":"https://arxiv.org/abs/1906.09607v3","title":"Densely Connected Search Space for More Flexible Neural Architecture Search","url_on_a_paper_host":true},"code_snippet_url":"https://github.com/JaminFong/DenseNAS/blob/e479206f9d73808d4167c669bb1d045a73b6f470/models/search_space_mbv2.py#L7","code_snippet_url_on_a_code_host":true,"categories":[{"area":"Computer Vision","area_id":"computer-vision","collection":"Convolutional Neural Networks","url":"/methods/category/convolutional-neural-networks","pwc_aliases":[]}],"n_papers_tagged":1,"archive_num_papers":null,"papers_newest_first":[{"paper":"/paper/densely-connected-search-space-for-more","title":"Densely Connected Search Space for More Flexible Neural Architecture Search","date":"2019-06-23","arxiv_id":"1906.09607","n_code_links":1,"syntology":{"ran":2,"of":2,"unverified":0,"pointer_only":0}}],"papers_shown":1,"tasks":[{"task":"/task/image-classification","name":"Image Classification","papers":1},{"task":"/task/architecture-search","name":"Neural Architecture Search","papers":1}],"tasks_shown":2,"n_tasks":2,"usage_by_year":[{"year":"2019","papers":1}],"row_source":"embedded","archive":{"source":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","archive_url":"https://paperswithcode.com/method/densenas-c"},"syntology_read_at":"2026-09-24T18:15:14+00:00"}