What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Operating system
- Electrical engineering
Sanghoon Lee focuses on Artificial intelligence, Computer vision, Electronic engineering, Human visual system model and Convolutional neural network.
His work deals with themes such as Video quality and Pattern recognition, which intersect with Artificial intelligence.
His Computer vision research is multidisciplinary, incorporating elements of Depth perception and Stereo display.
His Electronic engineering research includes themes of Audio signal flow, Electrical engineering and Noise figure.
His Human visual system model research incorporates elements of Reduction, Motion estimation, Visual perception, Wavelet transform and Scene statistics.
His Convolutional neural network study combines topics from a wide range of disciplines, such as Waveform, Intelligent sensor, Support vector machine and Gesture.
His most cited work include:
- Non-orthogonal Multiple Access in a Downlink Multiuser Beamforming System (275 citations)
- Method and apparatus for executing voice command in electronic device (207 citations)
- Ensemble Deep Learning for Skeleton-Based Action Recognition Using Temporal Sliding LSTM Networks (187 citations)
What are the main themes of his work throughout his whole career to date?
Sanghoon Lee mostly deals with Artificial intelligence, Computer vision, Electronic engineering, Electrical engineering and Optoelectronics.
His research on Artificial intelligence often connects related topics like Pattern recognition.
Computer vision is represented through his Stereoscopy and Image processing research.
He has researched Electronic engineering in several fields, including Computer network and Communication channel, Orthogonal frequency-division multiplexing.
His research related to Voltage and Signal might be considered part of Electrical engineering.
The study incorporates disciplines such as Layer and Substrate in addition to Optoelectronics.
He most often published in these fields:
- Artificial intelligence (20.23%)
- Computer vision (15.88%)
- Electronic engineering (13.32%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (20.23%)
- Computer vision (15.88%)
- Pattern recognition (4.35%)
In recent papers he was focusing on the following fields of study:
Sanghoon Lee mainly investigates Artificial intelligence, Computer vision, Pattern recognition, Convolutional neural network and Visualization.
His Artificial intelligence study frequently links to related topics such as Distortion.
His Computer vision course of study focuses on Display size and Display resolution.
His studies in Convolutional neural network integrate themes in fields like Image quality and Visual perception.
His biological study deals with issues like Stereoscopy, which deal with fields such as Salience.
Sanghoon Lee interconnects Quality and Algorithm in the investigation of issues within Feature extraction.
Between 2015 and 2021, his most popular works were:
- Ensemble Deep Learning for Skeleton-Based Action Recognition Using Temporal Sliding LSTM Networks (187 citations)
- Fully Deep Blind Image Quality Predictor (179 citations)
- Deep Convolutional Neural Models for Picture-Quality Prediction: Challenges and Solutions to Data-Driven Image Quality Assessment (126 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Electrical engineering
His scientific interests lie mostly in Artificial intelligence, Computer vision, Convolutional neural network, Feature extraction and Visualization.
The study of Artificial intelligence is intertwined with the study of Pattern recognition in a number of ways.
The Computer vision study combines topics in areas such as Robustness, Virtual reality, High-definition video and Stereo display.
His work in Convolutional neural network covers topics such as Visual perception which are related to areas like Digital image and Vision science.
In Feature extraction, Sanghoon Lee works on issues like Quality, which are connected to Nonlinear distortion and Transform coding.
Sanghoon Lee has included themes like Monocular and Fixation in his Visualization study.
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