Yang Yang focuses on Artificial intelligence, Hash function, Pattern recognition, Theoretical computer science and K-independent hashing. His Artificial intelligence study frequently links to related topics such as Machine learning. His Machine learning study integrates concerns from other disciplines, such as Adversarial system, Subspace topology, Modal, Classifier and Adversarial information retrieval.
The concepts of his Hash function study are interwoven with issues in Image retrieval, Visual Word and Nearest neighbor search. His Discriminative model study in the realm of Pattern recognition connects with subjects such as Matrix decomposition. His work deals with themes such as Feature hashing, Universal hashing and Dynamic perfect hashing, which intersect with K-independent hashing.
His primary areas of investigation include Artificial intelligence, Pattern recognition, Machine learning, Hash function and Information retrieval. The study of Artificial intelligence is intertwined with the study of Computer vision in a number of ways. Yang Yang interconnects Radar and Subspace topology in the investigation of issues within Pattern recognition.
His Machine learning research is multidisciplinary, relying on both Representation, Classifier and Modal. His Hash function research includes themes of Theoretical computer science and Image retrieval. Yang Yang has included themes like Semantics and Visualization in his Feature extraction study.
His scientific interests lie mostly in Artificial intelligence, Machine learning, Pattern recognition, Severe acute respiratory syndrome coronavirus 2 and Virology. His research on Artificial intelligence often connects related areas such as Modal. His studies in Machine learning integrate themes in fields like Generative grammar and Robustness.
Yang Yang studied Pattern recognition and Image retrieval that intersect with Embedding and Theoretical computer science. His Deep learning study combines topics in areas such as Hash function and Data set. His work on Hypoalbuminemia and Angiotensin II is typically connected to Bronchoalveolar lavage, Sputum and Nasal Swab as part of general Internal medicine study, connecting several disciplines of science.
His main research concerns Artificial intelligence, Severe acute respiratory syndrome coronavirus 2, Machine learning, Coronavirus and Internal medicine. His study connects Pattern recognition and Artificial intelligence. The concepts of his Pattern recognition study are interwoven with issues in Micro doppler and Bistatic radar.
His work carried out in the field of Machine learning brings together such families of science as Variety, Coarse to fine, Conditional entropy and Context knowledge. His study focuses on the intersection of Internal medicine and fields such as Gastroenterology with connections in the field of Virus and Respiratory system. In Deep learning, Yang Yang works on issues like Scalability, which are connected to Hash function.
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Treatment of 5 Critically Ill Patients With COVID-19 With Convalescent Plasma.
Chenguang Shen;Zhaoqin Wang;Fang Zhao;Yang Yang.
Clinical and biochemical indexes from 2019-nCoV infected patients linked to viral loads and lung injury.
Yingxia Liu;Yang Yang;Cong Zhang;Cong Zhang;Fengming Huang.
Science China-life Sciences (2020)
Experimental Treatment with Favipiravir for COVID-19: An Open-Label Control Study.
Qingxian Cai;Minghui Yang;Dongjing Liu;Jun Chen.
Evaluating the accuracy of different respiratory specimens in the laboratory diagnosis and monitoring the viral shedding of 2019-nCoV infections
Yang Yang;Minghui Yang;Chenguang Shen;Fuxiang Wang.
Inter-media hashing for large-scale retrieval from heterogeneous data sources
Jingkuan Song;Yang Yang;Yi Yang;Zi Huang.
international conference on management of data (2013)
Adversarial Cross-Modal Retrieval
Bokun Wang;Yang Yang;Xing Xu;Alan Hanjalic.
acm multimedia (2017)
Plasma IP-10 and MCP-3 levels are highly associated with disease severity and predict the progression of COVID-19.
Yang Yang;Chenguang Shen;Jinxiu Li;Jing Yuan.
The Journal of Allergy and Clinical Immunology (2020)
Learning Discriminative Binary Codes for Large-scale Cross-modal Retrieval
Xing Xu;Fumin Shen;Yang Yang;Heng Tao Shen.
IEEE Transactions on Image Processing (2017)
Unsupervised Deep Hashing with Similarity-Adaptive and Discrete Optimization
Fumin Shen;Yan Xu;Li Liu;Yang Yang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2018)
Self-taught dimensionality reduction on the high-dimensional small-sized data
Xiaofeng Zhu;Zi Huang;Yang Yang;Heng Tao Shen.
Pattern Recognition (2013)
Profile was last updated on December 6th, 2021.
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