乐胖代购免代理版

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Zero\u2010shot learning (ZSL) is a general solution for incorporating prior knowledge into data\u2010driven models and achieving accurate class identification. The combination of the two, known as multimodal ZSL (MZSL), can fully exploit the advantages of both technologies and is expected to produce models with greater generalization ability. However, the MZSL algorithms and applications have not yet been thoroughly investigated and summarized. This study fills this gap by providing an objective overview of MZSL's definition, typical algorithms, representative applications, and critical issues. This article will not only provide researchers in this field with a comprehensive perspective, but it will also highlight several promising research directions.<\/jats:p>This article is categorized under:\nAlgorithmic Development > Multimedia<\/jats:p><\/jats:list-item>\nTechnologies > Classification<\/jats:p><\/jats:list-item>\nTechnologies > Machine Learning<\/jats:p><\/jats:list-item>\n<\/jats:list><\/jats:p>","DOI":"10.1002\/widm.1488","type":"journal-article","created":{"date-parts":[[2023,1,20]],"date-time":"2023-01-20T10:44:20Z","timestamp":1674211460000},"update-policy":"http:\/\/dx.doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["A review on multimodal zero\u2010shot learning"],"prefix":"10.1002","volume":"13","author":[{"ORCID":"http:\/\/orcid.org\/0000-0003-2414-6066","authenticated-orcid":false,"given":"Weipeng","family":"Cao","sequence":"first","affiliation":[{"name":"Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ) Shenzhen China"}]},{"given":"Yuhao","family":"Wu","sequence":"additional","affiliation":[{"name":"Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ) Shenzhen China"}]},{"given":"Yixuan","family":"Sun","sequence":"additional","affiliation":[{"name":"Anhui University New York Stony Brook College Anhui University Hefei China"}]},{"given":"Haigang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Applied Artificial Intelligence of the Guangdong\u2010Hong Kong\u2010Macao Greater Bay Area Shenzhen Polytechnic Shenzhen China"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-2511-8318","authenticated-orcid":false,"given":"Jin","family":"Ren","sequence":"additional","affiliation":[{"name":"Institute of Applied Artificial Intelligence of the Guangdong\u2010Hong Kong\u2010Macao Greater Bay Area Shenzhen Polytechnic Shenzhen China"}]},{"given":"Dujuan","family":"Gu","sequence":"additional","affiliation":[{"name":"NSFOCUS Technologies Group Co., Ltd Beijing China"}]},{"given":"Xingkai","family":"Wang","sequence":"additional","affiliation":[{"name":"NSFOCUS Technologies Group Co., Ltd Beijing China"}]}],"member":"311","published-online":{"date-parts":[[2023,1,20]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2487986"},{"key":"e_1_2_10_3_1","first-page":"24206","article-title":"Vatt: Transformers for multimodal self\u2010supervised learning from raw video, audio and text","volume":"34","author":"Akbari H.","year":"2021","journal-title":"Proceedings of the Advances in Neural Information Processing Systems"},{"key":"e_1_2_10_4_1","doi-asserted-by":"crossref","unstructured":"Annadani Y. &Biswas S.(2018).Preserving semantic relations for zero\u2010shot learning. 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