{"type":"ScholarlyArticle","title":"Learning from Multimedia Data with Incomplete Information","authors":[{"name":"Renshuai Tao","slug":"renshuai-tao","given":"Renshuai","family":"Tao","affiliation":""}],"abstract":"Traditional deep learning methods are based on the condition that the data is of high-quality, which means the data information is highly available. However, data in these scenes often have the characteristics of large background noise, lack of sample content, small target, serious occlusion and a small number of samples. The application of related tasks in real open scenarios is very important, so it is urgent to make full use of these incomplete information data accurately.","doi":"10.24963/ijcai.2021/692","url":"https://ijcai.org/proceedings/2021/692","pdf":"https://ijcai.org/proceedings/2021/0692.pdf","markdown":"https://ijcai.org/proceedings/2021/692.md","bibtex":"https://ijcai.org/proceedings/2021/bibtex/692","volume":{"slug":"2021","title":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2021","url":"https://ijcai.org/proceedings/2021/","year":2021,"location":"Montreal","dates":"19-27 August 2021","editors":"Prof. Zhi-Hua Zhou","isbn":"978-0-9992411-9-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2021"},"section":"Doctoral Consortium","track":"Doctoral Consortium","number":692,"pages":{"first":4921,"last":4922},"keywords":["Computer Vision: Recognition: Detection, Categorization, Indexing, Matching, Retrieval, Semantic Interpretation","Machine Learning: Deep Learning","Data Mining: Feature Extraction, Selection and Dimensionality Reduction","Computer Vision: Language and Vision"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}