What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Operating system
Sukhan Lee spends much of his time researching Artificial intelligence, Computer vision, Control theory, Assembly planning and Nozzle.
His studies deal with areas such as Coding, Error detection and correction and Pattern recognition as well as Artificial intelligence.
His study in Computer vision is interdisciplinary in nature, drawing from both Kalman filter and Invariant extended Kalman filter.
His Control theory research incorporates themes from Robot, Point, Cartesian coordinate system and Robot control.
Sukhan Lee combines subjects such as Computer-aided and Motion planning with his study of Assembly planning.
His Nozzle study combines topics in areas such as Contact angle, Electrospray, Polymer and Argon.
His most cited work include:
- OSIRIS: A Three-Dimensional, Fully Relativistic Particle in Cell Code for Modeling Plasma Based Accelerators (459 citations)
- A Gaussian potential function network with hierarchically self-organizing learning (299 citations)
- Electronic pen input device and coordinate detecting method therefor (167 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Artificial intelligence, Computer vision, Robot, Control theory and Pattern recognition.
His Artificial intelligence study focuses mostly on Feature extraction, Pose, Object, Point cloud and Robustness.
Many of his studies on Pose apply to Cognitive neuroscience of visual object recognition as well.
His research in Structured light, Pixel, Stereo camera and Projector are components of Computer vision.
Robot and Human–computer interaction are frequently intertwined in his study.
His Control theory research focuses on Control engineering and how it relates to Control system.
He most often published in these fields:
- Artificial intelligence (43.30%)
- Computer vision (26.41%)
- Robot (16.70%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (43.30%)
- Computer vision (26.41%)
- Pattern recognition (8.74%)
In recent papers he was focusing on the following fields of study:
Sukhan Lee focuses on Artificial intelligence, Computer vision, Pattern recognition, Structured light and Pixel.
His study in Point cloud, Feature extraction, Deep learning, Image and Representation falls under the purview of Artificial intelligence.
His work on Pose as part of general Computer vision study is frequently connected to Set, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His Pattern recognition study incorporates themes from Signal strength, Image translation, Real-time computing, Invariant and RSS.
His biological study spans a wide range of topics, including 3D reconstruction, 3d camera, Projection, Boundary and Projector.
His Pixel research integrates issues from Image resolution, Image sensor and Sun sensor.
Between 2014 and 2021, his most popular works were:
- A Comprehensive Survey of Driving Monitoring and Assistance Systems. (33 citations)
- Dark side of comet 67P/Churyumov-Gerasimenko in Aug.–Oct. 2014 - MIRO/Rosetta continuum observations of polar night in the southern regions (33 citations)
- Distributed Multisensor Data Fusion under Unknown Correlation and Data Inconsistency. (30 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Operating system
- Computer vision
Sukhan Lee mainly investigates Artificial intelligence, Pattern recognition, Computer vision, Sensor fusion and Projection.
His work deals with themes such as Real-time computing, Invariant and Signal strength, which intersect with Artificial intelligence.
Sukhan Lee has included themes like RSS, Feature, Autoencoder and Bayesian probability in his Pattern recognition study.
His Sensor fusion research incorporates elements of Minimum mean square error, Algorithm, Covariance and Correlation.
In his study, which falls under the umbrella issue of Algorithm, Outlier is strongly linked to Wireless sensor network.
The Projection study combines topics in areas such as Frame rate, Single camera, Camera resectioning, Field-programmable gate array and Projector.
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.
