What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
Jaihie Kim mainly investigates Artificial intelligence, Computer vision, Pattern recognition, Biometrics and Feature extraction.
His study in Artificial intelligence concentrates on Iris recognition, Orientation, Fingerprint, Fingerprint recognition and Word error rate.
His Computer vision study frequently draws parallels with other fields, such as Iris.
His studies deal with areas such as IRIS and Feature as well as Pattern recognition.
The various areas that Jaihie Kim examines in his Biometrics study include Classifier, Image segmentation and Data mining.
His Feature extraction research includes themes of Face, Liveness, Local binary patterns, Image texture and Iterative reconstruction.
His most cited work include:
- Extreme Learning Machine (558 citations)
- Age estimation using a hierarchical classifier based on global and local facial features (186 citations)
- Iris feature extraction using independent component analysis (129 citations)
What are the main themes of his work throughout his whole career to date?
Jaihie Kim mainly focuses on Artificial intelligence, Computer vision, Pattern recognition, Biometrics and Face.
His work on Artificial intelligence deals in particular with Fingerprint recognition, Feature extraction, Iris recognition, Feature and Facial recognition system.
His Feature extraction study combines topics in areas such as Linear discriminant analysis and Word error rate.
His study in Pattern recognition is interdisciplinary in nature, drawing from both Matching and Speech recognition.
The study incorporates disciplines such as Independent component analysis, Data mining and Cryptography in addition to Biometrics.
In his research, Orientation is intimately related to Minutiae, which falls under the overarching field of Fingerprint.
He most often published in these fields:
- Artificial intelligence (88.94%)
- Computer vision (70.05%)
- Pattern recognition (29.95%)
What were the highlights of his more recent work (between 2012-2020)?
- Artificial intelligence (88.94%)
- Computer vision (70.05%)
- Pattern recognition (29.95%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Artificial intelligence, Computer vision, Pattern recognition, Fingerprint and Face.
His study in Fingerprint recognition, Feature, Biometrics, Image and Iris recognition is carried out as part of his Artificial intelligence studies.
His research on Computer vision frequently connects to adjacent areas such as Iris.
His Pattern recognition research is multidisciplinary, incorporating elements of Minutiae, Filter and Fingerprint detection.
Enhanced Data Rates for GSM Evolution is closely connected to Fingerprint in his research, which is encompassed under the umbrella topic of Fingerprint.
His study in the field of Facial recognition system and Object-class detection also crosses realms of Age estimation, Demography and Psychology.
Between 2012 and 2020, his most popular works were:
- Extreme Learning Machine (558 citations)
- Detecting driver drowsiness using feature-level fusion and user-specific classification (86 citations)
- Palmprint recognition with Local Micro-structure Tetra Pattern (35 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
His primary areas of investigation include Artificial intelligence, Computer vision, Pattern recognition, Biometrics and Fingerprint.
His work on Feature, Gesture recognition and Adaptive learning as part of general Artificial intelligence research is frequently linked to Point and Mobile device, thereby connecting diverse disciplines of science.
His research in Computer vision intersects with topics in Word error rate and Mobile phone.
His research links Filter with Pattern recognition.
The Biometrics study combines topics in areas such as Password, Histogram, Linear discriminant analysis, Kernel and Feature extraction.
His Fingerprint research integrates issues from Gabor filter, Local binary patterns, Texture and Fingerprint.
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