Huazhu Fu mainly focuses on Artificial intelligence, Pattern recognition, Computer vision, Segmentation and Image segmentation. His work on Deep learning, Feature extraction, Salient and Cluster analysis as part of general Artificial intelligence study is frequently connected to Constraint, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. As a part of the same scientific study, Huazhu Fu usually deals with the Pattern recognition, concentrating on RGB color model and frequently concerns with Saliency map, Feature matching and Mutual exclusion.
His Computer vision research is multidisciplinary, relying on both Representation and Identification. The various areas that Huazhu Fu examines in his Segmentation study include Object and Object based. His work focuses on many connections between Image segmentation and other disciplines, such as Glaucoma, that overlap with his field of interest in Fundus and Optical imaging.
Huazhu Fu mainly investigates Artificial intelligence, Pattern recognition, Computer vision, Segmentation and Deep learning. His Glaucoma research extends to the thematically linked field of Artificial intelligence. His Pattern recognition study combines topics in areas such as RGB color model, Focus, Leverage and Cluster analysis.
His work in the fields of Image overlaps with other areas such as Constraint. His Segmentation study integrates concerns from other disciplines, such as Pixel and Fundus, Optic disc, Optic cup. His Deep learning research incorporates themes from Image processing, Robustness and Color space.
His main research concerns Artificial intelligence, Segmentation, Pattern recognition, Deep learning and Machine learning. His work carried out in the field of Artificial intelligence brings together such families of science as Fundus and Computer vision. His Computer vision study incorporates themes from Salient, Code and Salience.
His Segmentation research integrates issues from Discriminative model and Similarity. He combines subjects such as Image, Feature, Medical diagnosis and Hash function with his study of Pattern recognition. His Image segmentation research includes elements of Retinal and Optical coherence tomography.
Huazhu Fu focuses on Artificial intelligence, Machine learning, Field, Deep learning and Feature extraction. The Artificial intelligence study combines topics in areas such as Fundus and Computer vision. His research in Computer vision intersects with topics in Salience and Code.
His work deals with themes such as Salient object detection, Robustness and Taxonomy, which intersect with Machine learning. The study incorporates disciplines such as Depth map, Salient, Convolutional neural network and Object detection in addition to Feature extraction. Huazhu Fu has researched Image segmentation in several fields, including Pixel, Optical coherence tomography and Retinal.
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CE-Net: Context Encoder Network for 2D Medical Image Segmentation
Zaiwang Gu;Jun Cheng;Huazhu Fu;Kang Zhou.
IEEE Transactions on Medical Imaging (2019)
Cluster-Based Co-Saliency Detection
Huazhu Fu;Xiaochun Cao;Zhuowen Tu.
IEEE Transactions on Image Processing (2013)
Diversity-induced Multi-view Subspace Clustering
Xiaochun Cao;Changqing Zhang;Huazhu Fu;Si Liu.
computer vision and pattern recognition (2015)
Joint Optic Disc and Cup Segmentation Based on Multi-Label Deep Network and Polar Transformation
Huazhu Fu;Jun Cheng;Yanwu Xu;Damon Wing Kee Wong.
IEEE Transactions on Medical Imaging (2018)
DeepVessel: Retinal Vessel Segmentation via Deep Learning and Conditional Random Field
Huazhu Fu;Yanwu Xu;Stephen Lin;Damon Wing Kee Wong.
medical image computing and computer assisted intervention (2016)
Retinal vessel segmentation via deep learning network and fully-connected conditional random fields
Huazhu Fu;Yanwu Xu;Damon Wing Kee Wong;Jiang Liu.
international symposium on biomedical imaging (2016)
Low-Rank Tensor Constrained Multiview Subspace Clustering
Changqing Zhang;Huazhu Fu;Si Liu;Guangcan Liu.
international conference on computer vision (2015)
Generalized Latent Multi-View Subspace Clustering
Changqing Zhang;Huazhu Fu;Qinghua Hu;Xiaochun Cao.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2020)
Latent Multi-view Subspace Clustering
Changqing Zhang;Qinghua Hu;Huazhu Fu;Pengfei Zhu.
computer vision and pattern recognition (2017)
Disc-Aware Ensemble Network for Glaucoma Screening From Fundus Image
Huazhu Fu;Jun Cheng;Yanwu Xu;Changqing Zhang.
IEEE Transactions on Medical Imaging (2018)
Profile was last updated on December 6th, 2021.
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