Artificial intelligence, Data mining, Pattern recognition, Machine learning and Computer vision are his primary areas of study. His work on Artificial intelligence deals in particular with Artificial neural network, Feature extraction, Embedding, Outlier and Deep learning. His Data mining research incorporates themes from Hidden Markov model, Side information, Statistical model and Cluster analysis.
His study in Cluster analysis is interdisciplinary in nature, drawing from both Unsupervised learning and Identification. Zhongfei Zhang has researched Pattern recognition in several fields, including Subspace topology, Content-based image retrieval, Automatic image annotation, Image retrieval and Covariance matrix. His Machine learning research includes elements of Representation, Multimedia information retrieval and Multiple view.
His primary areas of investigation include Artificial intelligence, Machine learning, Pattern recognition, Data mining and Computer vision. His is doing research in Discriminative model, Benchmark, Convolutional neural network, Feature extraction and Automatic image annotation, both of which are found in Artificial intelligence. His Automatic image annotation research focuses on Information retrieval and how it connects with Web page.
Machine learning is often connected to Embedding in his work. His research integrates issues of Contextual image classification, Subspace topology and Image retrieval in his study of Pattern recognition. His Data mining study which covers Cluster analysis that intersects with Relational database.
His primary scientific interests are in Artificial intelligence, Machine learning, Benchmark, Artificial neural network and Discriminative model. His Artificial intelligence study frequently links to related topics such as Pattern recognition. His work investigates the relationship between Machine learning and topics such as Robustness that intersect with problems in Deep learning and Feature extraction.
His Benchmark study integrates concerns from other disciplines, such as DUAL and Tensor. Zhongfei Zhang has included themes like Algorithm, Facial recognition system and Hypersphere in his Artificial neural network study. His Discriminative model study deals with Class intersecting with Triplet loss, Shot, Prototype learning and Autoencoder.
Zhongfei Zhang mostly deals with Artificial intelligence, Machine learning, Benchmark, Semantics and Zero shot learning. His Data modeling research extends to Artificial intelligence, which is thematically connected. His Data modeling research is multidisciplinary, incorporating perspectives in Field, Feature learning, Neural coding, Markov chain and Convolutional neural network.
His Machine learning study combines topics from a wide range of disciplines, such as Representation and Representation. His research in Semantics intersects with topics in Embedding and Visualization. His Discriminative model study combines topics in areas such as Class, Inference and Generative model.
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A survey of appearance models in visual object tracking
Xi Li;Weiming Hu;Chunhua Shen;Zhongfei Zhang.
ACM Transactions on Intelligent Systems and Technology (2013)
Spectral clustering for multi-type relational data
Bo Long;Zhongfei (Mark) Zhang;Xiaoyun Wú;Philip S. Yu.
international conference on machine learning (2006)
A general model for multiple view unsupervised learning
Bo Long;Philip S. Yu;Zhongfei (Mark) Zhang.
siam international conference on data mining (2008)
Spatial color histograms for content-based image retrieval
Aibing Rao;R.K. Srihari;Zhongfei Zhang.
international conference on tools with artificial intelligence (1999)
Co-clustering by block value decomposition
Bo Long;Zhongfei (Mark) Zhang;Philip S. Yu.
knowledge discovery and data mining (2005)
Unsupervised learning on k-partite graphs
Bo Long;Xiaoyun Wu;Zhongfei (Mark) Zhang;Philip S. Yu.
knowledge discovery and data mining (2006)
Intelligent Indexing and Semantic Retrieval of Multimodal Documents
Rohini K. Srihari;Zhongfei Zhang;Aibing Rao.
Information Retrieval (2000)
A probabilistic semantic model for image annotation and multimodal image retrieval
Ruofei Zhang;Zhongfei Zhang;Mingjing Li;Wei-Ying Ma.
international conference on computer vision (2005)
Visual tracking via incremental Log-Euclidean Riemannian subspace learning
Xi Li;Weiming Hu;Zhongfei Zhang;Xiaoqin Zhang.
computer vision and pattern recognition (2008)
Robust Visual Tracking Based on Incremental Tensor Subspace Learning
Xi Li;Weiming Hu;Zhongfei Zhang;Xiaoqin Zhang.
international conference on computer vision (2007)
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