What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Computer vision
The scientist’s investigation covers issues in Biometrics, Artificial intelligence, Pattern recognition, Computer security and Data mining.
His research in Biometrics intersects with topics in Hash function, Theoretical computer science, Feature and Authentication.
His Artificial intelligence study frequently intersects with other fields, such as Computer vision.
His studies examine the connections between Pattern recognition and genetics, as well as such issues in Word error rate, with regards to Multi-factor authentication.
Andrew Beng Jin Teoh combines subjects such as Code, Minutiae, One-time password and Fingerprint with his study of Data mining.
His Password study combines topics in areas such as Identity theft, Cryptography and Access control.
His most cited work include:
- Extreme Learning Machine (558 citations)
- Random Multispace Quantization as an Analytic Mechanism for BioHashing of Biometric and Random Identity Inputs (364 citations)
- A survey of keystroke dynamics biometrics (194 citations)
What are the main themes of his work throughout his whole career to date?
Andrew Beng Jin Teoh spends much of his time researching Artificial intelligence, Pattern recognition, Biometrics, Facial recognition system and Computer vision.
His work on Wavelet as part of general Pattern recognition study is frequently linked to Discretization, therefore connecting diverse disciplines of science.
His Biometrics research includes elements of Fingerprint, Hash function, Theoretical computer science and Data mining.
His studies deal with areas such as Key and Encryption as well as Theoretical computer science.
His work deals with themes such as Extreme learning machine, Covariance matrix and Non-negative matrix factorization, which intersect with Facial recognition system.
The Password study which covers Security token that intersects with Cryptography.
He most often published in these fields:
- Artificial intelligence (70.80%)
- Pattern recognition (56.80%)
- Biometrics (54.00%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (70.80%)
- Pattern recognition (56.80%)
- Biometrics (54.00%)
In recent papers he was focusing on the following fields of study:
Andrew Beng Jin Teoh focuses on Artificial intelligence, Pattern recognition, Biometrics, Hash function and Face.
He focuses mostly in the field of Artificial intelligence, narrowing it down to matters related to Smoothing and, in some cases, Human eye.
His Pattern recognition study combines topics in areas such as Artificial neural network, Feature and Metric.
His Biometrics study incorporates themes from Fingerprint, Deep learning, Theoretical computer science and Salient.
The various areas that he examines in his Hash function study include Supervised learning and Feature.
His Facial recognition system course of study focuses on Principal component analysis and Extreme learning machine.
Between 2018 and 2021, his most popular works were:
- Cancelable fingerprint template design with randomized non-negative least squares (23 citations)
- Multi-Fold Gabor, PCA, and ICA Filter Convolution Descriptor for Face Recognition (21 citations)
- Periocular Recognition in the Wild with Orthogonal Combination of Local Binary Coded Pattern in Dual-stream Convolutional Neural Network (6 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Computer vision
His primary scientific interests are in Artificial intelligence, Pattern recognition, Biometrics, Facial recognition system and Principal component analysis.
His Artificial intelligence study frequently draws connections to adjacent fields such as Computer vision.
His research in Pattern recognition intersects with topics in Cuckoo hashing, Hash table, Perceptron and Authentication.
He has researched Biometrics in several fields, including Hash function, Minutiae and Feature.
His Facial recognition system research integrates issues from Visualization, Leverage and Gabor wavelet.
Andrew Beng Jin Teoh interconnects Gabor filter, Independent component analysis, Histogram and Convolution in the investigation of issues within Principal component analysis.
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