Linjun Yang focuses on Information retrieval, Ranking, Relevance, Feature and Image. His research on Information retrieval often connects related areas such as Modality. The Ranking study combines topics in areas such as Ranking, Full text search and Feature set.
His Ranking study combines topics from a wide range of disciplines, such as Social media and Similarity. His Relevance research integrates issues from Multimedia, The Internet and Service. He has included themes like Video tracking, Histogram, User profile and Inverted index in his Feature study.
Linjun Yang mainly focuses on Information retrieval, Artificial intelligence, Machine learning, Ranking and Pattern recognition. His studies deal with areas such as Image retrieval and Visual Word as well as Information retrieval. In general Artificial intelligence, his work in Feature extraction, Image and Feature is often linked to TRECVID linking many areas of study.
His biological study spans a wide range of topics, including Ranking, Full text search, Web page and Data mining. Linjun Yang interconnects Contextual image classification, Embedding and Cluster analysis in the investigation of issues within Pattern recognition. Linjun Yang has researched Relevance in several fields, including Online video and Multimedia.
Linjun Yang spends much of his time researching Information retrieval, Artificial intelligence, World Wide Web, The Internet and Search engine. His Image retrieval research extends to the thematically linked field of Information retrieval. The various areas that he examines in his Artificial intelligence study include Machine learning, Computer vision and Pattern recognition.
His work in the fields of Search-oriented architecture overlaps with other areas such as Bridging. His biological study deals with issues like Automatic summarization, which deal with fields such as Data mining. Linjun Yang has researched Ranking in several fields, including Search analytics, Concept search and Search engine indexing.
Upload, Feature, Data mining, World Wide Web and Information retrieval are his primary areas of study. Linjun Yang combines subjects such as Social media and The Internet with his study of Upload. Linjun Yang integrates Feature with Assisted GPS in his research.
The study incorporates disciplines such as Ranking, Object, Relevance and Visual Word in addition to Data mining. His research in the fields of Semantic search and Search engine overlaps with other disciplines such as Bridging. His Information retrieval study incorporates themes from Language model and Automatic image annotation, Image retrieval.
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Dong Liu;Xian-Sheng Hua;Linjun Yang;Meng Wang.
the web conference (2009)
Learning to tag
Lei Wu;Linjun Yang;Nenghai Yu;Xian-Sheng Hua.
the web conference (2009)
CleanNet: Transfer Learning for Scalable Image Classifier Training with Label Noise
Kuang-Huei Lee;Xiaodong He;Lei Zhang;Linjun Yang.
computer vision and pattern recognition (2018)
Ensemble Manifold Regularization
Bo Geng;Dacheng Tao;Chao Xu;Linjun Yang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2012)
Media Tag Recommendation Technologies
Linjun Yang;Lei Wu;Xian-Sheng Hua.
Visual query suggestion
Zheng-Jun Zha;Linjun Yang;Tao Mei;Meng Wang.
acm multimedia (2009)
VideoSense: towards effective online video advertising
Tao Mei;Xian-Sheng Hua;Linjun Yang;Shipeng Li.
acm multimedia (2007)
Bayesian video search reranking
Xinmei Tian;Linjun Yang;Jingdong Wang;Yichen Yang.
acm multimedia (2008)
Online video recommendation based on multimodal fusion and relevance feedback
Bo Yang;Tao Mei;Xian-Sheng Hua;Linjun Yang.
conference on image and video retrieval (2007)
Automatic video recommendation
Tao Mei;Xian-Sheng Hua;Bo Yang;Linjun Yang.
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