What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Algorithm
His primary areas of investigation include Biometrics, Artificial intelligence, Pattern recognition, Speech recognition and Algorithm.
He has included themes like Fingerprint Verification Competition, Information privacy and Data mining in his Biometrics study.
His Artificial intelligence research includes themes of Quantization and Computer vision.
His Pattern recognition study integrates concerns from other disciplines, such as Matching, Sensor fusion, Outlier and Component.
His Speech recognition research is multidisciplinary, incorporating perspectives in Acoustics, Audio signal flow, Analog signal and Signal processing.
In general Algorithm, his work in Residual is often linked to Function, Mean value and Inclined plane linking many areas of study.
His most cited work include:
- Reducing audible spectral discontinuities (262 citations)
- Coder for incorporating extra information in a digital audio signal having a predetermined format, decoder for extracting such extra information from a digital signal, device for recording a digital signal on a record carrier, comprising such a coder, and record carrier obtained by means of such a device (216 citations)
- Device for transmitting data words representing a digitized analog signal and device for receiving the transmitted data words (150 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Artificial intelligence, Biometrics, Pattern recognition, Facial recognition system and Computer vision.
His Face, Classifier, Fingerprint recognition, Feature vector and Feature extraction investigations are all subjects of Artificial intelligence research.
In his research, Fuzzy logic is intimately related to Data mining, which falls under the overarching field of Biometrics.
His biological study deals with issues like Minutiae, which deal with fields such as Word error rate.
The concepts of his Facial recognition system study are interwoven with issues in Local binary patterns and Noise.
His work on Pixel and Image as part of general Computer vision study is frequently connected to Geography, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
He most often published in these fields:
- Artificial intelligence (52.48%)
- Biometrics (36.96%)
- Pattern recognition (34.98%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (52.48%)
- Biometrics (36.96%)
- Facial recognition system (26.07%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Artificial intelligence, Biometrics, Facial recognition system, Pattern recognition and Face.
His Artificial intelligence research is multidisciplinary, relying on both Machine learning, Process and Computer vision.
His research in Biometrics intersects with topics in Classifier, Data mining and Parametric statistics.
His studies deal with areas such as Feature extraction and Morphing as well as Facial recognition system.
His work deals with themes such as Image resolution, Image registration and Likelihood-ratio test, which intersect with Pattern recognition.
His Face research integrates issues from Local binary patterns and Noise.
Between 2014 and 2021, his most popular works were:
- Biometric Systems under Morphing Attacks: Assessment of Morphing Techniques and Vulnerability Reporting (47 citations)
- Towards Robust Evaluation of Face Morphing Detection (19 citations)
- Automatic Pulmonary Nodule Detection in CT Scans Using Convolutional Neural Networks Based on Maximum Intensity Projection (15 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Algorithm
Raymond N.J. Veldhuis focuses on Artificial intelligence, Facial recognition system, Biometrics, Face and Pattern recognition.
Many of his research projects under Artificial intelligence are closely connected to Workload with Workload, tying the diverse disciplines of science together.
His study in the fields of Three-dimensional face recognition and Face detection under the domain of Facial recognition system overlaps with other disciplines such as Low resolution.
His Biometrics research incorporates themes from Set, Process and Data mining.
His study focuses on the intersection of Face and fields such as Noise with connections in the field of Support vector machine, Pyramid, Pyramid, Color space and Local binary patterns.
His study in the field of Convolutional neural network also crosses realms of HSL and HSV.
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