What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Algorithm
Zhengguo Li mainly investigates Control theory, Algorithm, Artificial intelligence, Computer vision and Macroblock.
The Control theory study which covers Synchronization that intersects with Lyapunov function.
Zhengguo Li has researched Algorithm in several fields, including Signal compression, Histogram, Simulation and Reference frame.
His work on Image, Pixel and Exposure fusion is typically connected to Vector field as part of general Artificial intelligence study, connecting several disciplines of science.
His work on Image fusion as part of his general Computer vision study is frequently connected to Set, thereby bridging the divide between different branches of science.
His Macroblock research integrates issues from Coding tree unit, Variable bitrate, Constant bitrate, Context-adaptive binary arithmetic coding and Rate–distortion theory.
His most cited work include:
- Fast mode decision algorithm for intraprediction in H.264/AVC video coding (448 citations)
- Fast intermode decision in H.264/AVC video coding (294 citations)
- Weighted guided image filtering. (248 citations)
What are the main themes of his work throughout his whole career to date?
Zhengguo Li focuses on Artificial intelligence, Computer vision, Algorithm, Control theory and Pixel.
His research integrates issues of Dynamic range and Pattern recognition in his study of Artificial intelligence.
His study in the fields of High dynamic range, Smoothing, Composite image filter and Ghosting under the domain of Computer vision overlaps with other disciplines such as Intensity mapping.
His research investigates the link between Control theory and topics such as Synchronization that cross with problems in Chaotic and Secure communication.
Zhengguo Li has researched Pixel in several fields, including Histogram, Image segmentation, Computer graphics and Template matching.
His studies in Quantization integrate themes in fields like Data compression and Real-time computing.
He most often published in these fields:
- Artificial intelligence (52.44%)
- Computer vision (43.11%)
- Algorithm (19.56%)
What were the highlights of his more recent work (between 2016-2021)?
- Artificial intelligence (52.44%)
- Computer vision (43.11%)
- Image (14.22%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Computer vision, Image, Exposure fusion and Pattern recognition.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Smoothing and Dynamic range.
The various areas that Zhengguo Li examines in his Computer vision study include Colors of noise, Distortion and Odometry.
His work deals with themes such as Semantics, Construct and Iterative reconstruction, which intersect with Image.
His studies examine the connections between Exposure fusion and genetics, as well as such issues in Virtual image, with regards to Noise.
As a member of one scientific family, Zhengguo Li mostly works in the field of Pattern recognition, focusing on Feature and, on occasion, Pairwise comparison.
Between 2016 and 2021, his most popular works were:
- Detail-Enhanced Multi-Scale Exposure Fusion (48 citations)
- Single Image De-Hazing Using Globally Guided Image Filtering (39 citations)
- Multi-scale exposure fusion via gradient domain guided image filtering (33 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Algorithm
The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Image, Smoothing and Dynamic range.
His Artificial intelligence research incorporates themes from Covariance matrix and Linear system.
Zhengguo Li has included themes like Jacobian matrix and determinant and Odometry in his Computer vision study.
The study incorporates disciplines such as Pyramid, Filter and Edge-preserving smoothing in addition to Smoothing.
His Dynamic range research includes elements of Structure tensor and Composite image filter.
His study looks at the relationship between High dynamic range and topics such as Pyramid, which overlap with Range.
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