What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Computer vision
His primary scientific interests are in Artificial intelligence, Pattern recognition, Speech recognition, Electroencephalography and Computer vision.
Artificial intelligence is closely attributed to Machine learning in his study.
Seong-Whan Lee has researched Pattern recognition in several fields, including Artificial neural network, Facial recognition system, Face detection and Neuroimaging.
His research in Speech recognition intersects with topics in Stimulus, Sensorimotor rhythm, Decoding methods and Handwriting.
His Electroencephalography research includes themes of Resting state fMRI, Sensory stimulation therapy and Simulation.
His Pattern recognition study incorporates themes from Image processing and Tree, Algorithm, Computational complexity theory.
His most cited work include:
- Thinning methodologies-a comprehensive survey (1496 citations)
- The Role of Context for Object Detection and Semantic Segmentation in the Wild (737 citations)
- Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis. (419 citations)
What are the main themes of his work throughout his whole career to date?
Seong-Whan Lee focuses on Artificial intelligence, Pattern recognition, Computer vision, Electroencephalography and Speech recognition.
His study ties his expertise on Machine learning together with the subject of Artificial intelligence.
His research combines Feature and Pattern recognition.
His Electroencephalography research is multidisciplinary, incorporating perspectives in Stimulus, Decoding methods and Convolutional neural network.
His Speech recognition research is multidisciplinary, incorporating elements of Conditional random field, Event-related potential and Gesture, Gesture recognition.
His studies in Brain–computer interface integrate themes in fields like Control system and Robotic arm.
He most often published in these fields:
- Artificial intelligence (71.73%)
- Pattern recognition (35.13%)
- Computer vision (33.01%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (71.73%)
- Pattern recognition (35.13%)
- Electroencephalography (21.08%)
In recent papers he was focusing on the following fields of study:
Seong-Whan Lee spends much of his time researching Artificial intelligence, Pattern recognition, Electroencephalography, Brain–computer interface and Convolutional neural network.
He combines subjects such as Machine learning and Motor imagery with his study of Artificial intelligence.
His study in Pattern recognition is interdisciplinary in nature, drawing from both Image, Representation and Feature.
His research in Electroencephalography intersects with topics in Stimulus, Consciousness, Speech recognition, Decoding methods and Eye movement.
His studies deal with areas such as Imagined speech, Sequence, Relation and Event-related potential as well as Speech recognition.
His Brain–computer interface study also includes fields such as
- Computer vision most often made with reference to Robotic arm,
- Mental image which connect with Prefrontal cortex,
- Drone most often made with reference to Control system.
Between 2018 and 2021, his most popular works were:
- EEG dataset and OpenBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy. (60 citations)
- Subject-Independent Brain–Computer Interfaces Based on Deep Convolutional Neural Networks (52 citations)
- Strength and Similarity Guided Group-level Brain Functional Network Construction for MCI Diagnosis. (48 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Computer vision
His primary areas of study are Artificial intelligence, Pattern recognition, Electroencephalography, Brain–computer interface and Decoding methods.
Seong-Whan Lee regularly links together related areas like Machine learning in his Artificial intelligence studies.
The Pattern recognition study combines topics in areas such as Representation and Neuroimaging.
His research integrates issues of Preprocessor, Audiology and Eye movement in his study of Electroencephalography.
Seong-Whan Lee interconnects Control system, Mental image, Speech recognition, Bandwidth and Visualization in the investigation of issues within Brain–computer interface.
In his work, Remote sensing is strongly intertwined with Computer vision, which is a subfield of Deep learning.
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