What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Algorithm
- Computer vision
The scientist’s investigation covers issues in Algorithm, Artificial intelligence, Pattern recognition, Coding and Real-time computing.
His work deals with themes such as Motion vector and Color model, which intersect with Algorithm.
In his research, Stream cipher is intimately related to Computer vision, which falls under the overarching field of Artificial intelligence.
His Pattern recognition research incorporates themes from Image noise, Spatial analysis, Kernel and Robustness.
His Coding research incorporates elements of Low complexity, Encoder, Theoretical computer science and Random access.
The Real-time computing study which covers Context-adaptive binary arithmetic coding that intersects with Scalable Video Coding, Multiview Video Coding and Coding tree unit.
His most cited work include:
- Image segmentation by generalized hierarchical fuzzy C-means algorithm (375 citations)
- Huffman coding of DCT coefficients using dynamic codeword assignment and adaptive codebook selection (63 citations)
- Fast Mode Decision for H.264 with Variable Motion Block Sizes (43 citations)
What are the main themes of his work throughout his whole career to date?
Byeungwoo Jeon focuses on Artificial intelligence, Algorithm, Computer vision, Coding and Encoder.
His studies examine the connections between Artificial intelligence and genetics, as well as such issues in Pattern recognition, with regards to Robustness.
The various areas that Byeungwoo Jeon examines in his Algorithm study include Motion vector and Theoretical computer science.
His Coding study combines topics from a wide range of disciplines, such as Speech recognition, Data compression and Random access.
His biological study spans a wide range of topics, including Computational complexity theory, Soft-decision decoder and Parity bit.
His Coding tree unit research focuses on Context-adaptive binary arithmetic coding and how it relates to Real-time computing, Multiview Video Coding and Scalable Video Coding.
He most often published in these fields:
- Artificial intelligence (44.95%)
- Algorithm (41.69%)
- Computer vision (35.50%)
What were the highlights of his more recent work (between 2016-2021)?
- Artificial intelligence (44.95%)
- Computer vision (35.50%)
- Algorithm (41.69%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Computer vision, Algorithm, Pattern recognition and Hyperspectral imaging.
His Artificial intelligence study frequently involves adjacent topics like Filter.
He studied Computer vision and Near-infrared spectroscopy that intersect with Signal.
Algorithm is closely attributed to Coding in his study.
His Pattern recognition research includes elements of Spatial analysis and Cluster analysis.
His studies in Hyperspectral imaging integrate themes in fields like Subspace topology, Pixel, Low-rank approximation, Noise reduction and Image restoration.
Between 2016 and 2021, his most popular works were:
- Kernel quaternion principal component analysis and its application in RGB-D object recognition (42 citations)
- Hyperspectral Image Restoration Using Low-Rank Representation on Spectral Difference Image (34 citations)
- Low Rank Component Induced Spatial-Spectral Kernel Method for Hyperspectral Image Classification (31 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Computer vision
His primary scientific interests are in Artificial intelligence, Pattern recognition, Hyperspectral imaging, Computer vision and Pixel.
His study on Feature extraction, Principal component analysis, Feature selection and Hidden Markov model is often connected to Bayesian inference as part of broader study in Pattern recognition.
In his study, which falls under the umbrella issue of Computer vision, Sparse approximation and Lagrange multiplier is strongly linked to Compressed sensing.
In his research on the topic of Pixel, Image, Spatial analysis and Image resolution is strongly related with Regularization.
As a part of the same scientific study, Byeungwoo Jeon usually deals with the Kernel, concentrating on Quaternion and frequently concerns with Algorithm.
Many of his studies involve connections with topics such as YCbCr and Algorithm.
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