His primary areas of study are Artificial intelligence, Computer vision, Pattern recognition, Iterative reconstruction and Feature. Qionghai Dai has included themes like Machine learning and Graph in his Artificial intelligence study. Qionghai Dai has researched Computer vision in several fields, including Hyperspectral imaging and Surface reconstruction.
The concepts of his Pattern recognition study are interwoven with issues in Contextual image classification, Linear subspace, Categorization and Image retrieval. His study in Iterative reconstruction is interdisciplinary in nature, drawing from both Epipolar geometry, 3D reconstruction, Image resolution and Image texture. His work in Feature addresses subjects such as Visualization, which are connected to disciplines such as Stereoscopy, Representation and Image quality.
His scientific interests lie mostly in Artificial intelligence, Computer vision, Optics, Pattern recognition and Algorithm. His research on Artificial intelligence frequently connects to adjacent areas such as Machine learning. Light field, Depth map, Object, Image resolution and Multiview Video Coding are the subjects of his Computer vision studies.
Qionghai Dai combines subjects such as Phase retrieval and Fourier transform with his study of Optics. His study in Image retrieval extends to Pattern recognition with its themes.
His primary scientific interests are in Artificial intelligence, Optics, Computer vision, Artificial neural network and Light field. Artificial intelligence is frequently linked to Pattern recognition in his study. His work carried out in the field of Computer vision brings together such families of science as Frame and Hyperspectral imaging.
His studies deal with areas such as Epipolar geometry, Image stitching, Algorithm and Lens as well as Light field. His Microscope course of study focuses on Image sensor and Cardinal point, Relay lens, Image plane and Sample. His Scattering research is multidisciplinary, incorporating elements of Speckle pattern and Photon.
His main research concerns Artificial intelligence, Computer vision, Optics, Artificial neural network and Image resolution. In most of his Artificial intelligence studies, his work intersects topics such as Pattern recognition. He interconnects Image quality, Image, Quantization and Identification in the investigation of issues within Pattern recognition.
His research integrates issues of Image processing, Multiplexing and Phase modulation in his study of Optics. His Artificial neural network research integrates issues from Automatic control, Control theory, Control theory and Benchmark. His Image resolution research incorporates themes from Similarity, Grayscale, Frame rate, Interpolation and Image restoration.
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3-D Object Retrieval and Recognition With Hypergraph Analysis
Yue Gao;Meng Wang;Dacheng Tao;Rongrong Ji.
IEEE Transactions on Image Processing (2012)
Covariance discriminative learning: A natural and efficient approach to image set classification
Ruiping Wang;Huimin Guo;Larry S. Davis;Qionghai Dai.
computer vision and pattern recognition (2012)
Efficient Parallel Framework for HEVC Motion Estimation on Many-Core Processors
Chenggang Clarence Yan;Yongdong Zhang;Jizheng Xu;Feng Dai.
IEEE Transactions on Circuits and Systems for Video Technology (2014)
Deep Direct Reinforcement Learning for Financial Signal Representation and Trading
Yue Deng;Feng Bao;Youyong Kong;Zhiquan Ren.
IEEE Transactions on Neural Networks (2017)
A Highly Parallel Framework for HEVC Coding Unit Partitioning Tree Decision on Many-core Processors
Chenggang Yan;Yongdong Zhang;Jizheng Xu;Feng Dai.
IEEE Signal Processing Letters (2014)
WBSMDA: Within and Between Score for MiRNA-Disease Association prediction.
Xing Chen;Chenggang Clarence Yan;Chenggang Clarence Yan;Xu Zhang;Zhu-Hong You.
Scientific Reports (2016)
Light Field Image Processing: An Overview
Gaochang Wu;Belen Masia;Adrian Jarabo;Yuchen Zhang.
IEEE Journal of Selected Topics in Signal Processing (2017)
Camera Constraint-Free View-Based 3-D Object Retrieval
Yue Gao;Jinhui Tang;Richang Hong;Shuicheng Yan.
IEEE Transactions on Image Processing (2012)
Supervised Hash Coding With Deep Neural Network for Environment Perception of Intelligent Vehicles
Chenggang Yan;Hongtao Xie;Dongbao Yang;Jian Yin.
IEEE Transactions on Intelligent Transportation Systems (2018)
Less is More: Efficient 3-D Object Retrieval With Query View Selection
Yue Gao;Meng Wang;Zheng-Jun Zha;Qi Tian.
IEEE Transactions on Multimedia (2011)
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