2023 - Research.com Computer Science in China Leader Award
2019 - IEEE Fellow For contributions to image fusion and classification in remote sensing
His scientific interests lie mostly in Artificial intelligence, Computer vision, Pattern recognition, Image fusion and Pixel. His work investigates the relationship between Artificial intelligence and topics such as Machine learning that intersect with problems in Hyperspectral image classification. His Computer vision research incorporates elements of Classifier and Focus.
Support vector machine, Image segmentation and Contourlet are the core of his Pattern recognition study. In his study, Digital image processing is strongly linked to Feature detection, which falls under the umbrella field of Image fusion. His study looks at the relationship between Pixel and topics such as Principal component analysis, which overlap with Thematic Mapper.
His main research concerns Artificial intelligence, Pattern recognition, Hyperspectral imaging, Computer vision and Feature extraction. His is involved in several facets of Artificial intelligence study, as is seen by his studies on Pixel, Support vector machine, Sparse approximation, Image fusion and Image. His Image fusion research is multidisciplinary, relying on both Digital image processing, Panchromatic film, Contourlet, Focus and Sensor fusion.
His Pattern recognition research is multidisciplinary, incorporating elements of Image resolution and Multispectral image. Shutao Li studied Hyperspectral imaging and Anomaly detection that intersect with Detector. Shutao Li works mostly in the field of Feature extraction, limiting it down to topics relating to Feature and, in certain cases, Object detection.
Shutao Li mainly focuses on Artificial intelligence, Pattern recognition, Hyperspectral imaging, Feature extraction and Convolutional neural network. His Image resolution, Hyperspectral image classification, Iterative reconstruction, Deep learning and Image fusion investigations are all subjects of Artificial intelligence research. His Image fusion research is under the purview of Computer vision.
His work carried out in the field of Pattern recognition brings together such families of science as Pixel, Image, Spatial analysis and Multispectral image. His Hyperspectral imaging research also works with subjects such as
The scientist’s investigation covers issues in Hyperspectral imaging, Artificial intelligence, Pattern recognition, Feature extraction and Image resolution. His Hyperspectral imaging study combines topics from a wide range of disciplines, such as Matrix decomposition, Sparse matrix and Image processing. Shutao Li combines subjects such as Dynamic range and Computer vision with his study of Artificial intelligence.
Pattern recognition and Image are commonly linked in his work. His Feature extraction research includes themes of Smoothing, Convolutional neural network, Robustness and Hyperspectral image classification. His studies in Image resolution integrate themes in fields like Regularization and Multispectral image.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
ADASYN: Adaptive synthetic sampling approach for imbalanced learning
Haibo He;Yang Bai;E.A. Garcia;Shutao Li.
international joint conference on neural network (2008)
Image Fusion With Guided Filtering
Shutao Li;Xudong Kang;Jianwen Hu.
IEEE Transactions on Image Processing (2013)
Pixel-level image fusion
Shutao Li;Xudong Kang;Leyuan Fang;Jianwen Hu.
Information Fusion (2017)
Multifocus Image Fusion and Restoration With Sparse Representation
Bin Yang;Shutao Li.
IEEE Transactions on Instrumentation and Measurement (2010)
Spectral–Spatial Hyperspectral Image Classification With Edge-Preserving Filtering
Xudong Kang;Shutao Li;Jon Atli Benediktsson.
IEEE Transactions on Geoscience and Remote Sensing (2014)
Deep Learning for Hyperspectral Image Classification: An Overview
Shutao Li;Weiwei Song;Leyuan Fang;Yushi Chen.
IEEE Transactions on Geoscience and Remote Sensing (2019)
Performance comparison of different multi-resolution transforms for image fusion
Shutao Li;Bin Yang;Jianwen Hu.
Information Fusion (2011)
Multifocus image fusion using region segmentation and spatial frequency
Shutao Li;Bin Yang.
Image and Vision Computing (2008)
Combination of images with diverse focuses using the spatial frequency
Shutao Li;Shutao Li;James Tin-Yau Kwok;Yaonan Wang.
Information Fusion (2001)
Using the discrete wavelet frame transform to merge Landsat TM and SPOT panchromatic images
Shutao Li;Shutao Li;James T Kwok;Yaonan Wang.
Information Fusion (2002)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:
Hunan University
Hunan University
University of Iceland
Hong Kong University of Science and Technology
Sun Yat-sen University
University of Extremadura
Helmholtz-Zentrum Dresden-Rossendorf
University of Macau
South China University of Technology
University of Extremadura
Royal Institute of Technology
Silverbrook Research Pty Ltd
University of Minnesota
Monash University
University of Florida
University of Hawaii at Manoa
University of Saskatchewan
University of Arkansas at Fayetteville
University of Hertfordshire
Tsinghua University
Weizmann Institute of Science
University of Utah
George Mason University
The University of Texas Southwestern Medical Center
University of California, Berkeley
University of North Carolina at Chapel Hill