What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Algorithm
His primary areas of study are Digital watermarking, Multimedia, Watermark, Artificial intelligence and Computer vision.
Ton Kalker studies Digital watermarking, namely Copy protection.
Music identification, Electronic imaging and Closed captioning is closely connected to World Wide Web in his research, which is encompassed under the umbrella topic of Multimedia.
When carried out as part of a general Artificial intelligence research project, his work on Luminance and Projector is frequently linked to work in Video quality and Block size, therefore connecting diverse disciplines of study.
His Identification research is multidisciplinary, incorporating perspectives in Feature extraction, Hash function and Pattern recognition.
As part of the same scientific family, Ton Kalker usually focuses on Computer security, concentrating on Steganography and intersecting with Theoretical computer science.
His most cited work include:
- Digital Watermarking and Steganography (1323 citations)
- A Highly Robust Audio Fingerprinting System. (770 citations)
- Reversible Image Watermarking Based on Integer-to-Integer Wavelet Transform (317 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Digital watermarking, Watermark, Computer security, Artificial intelligence and Cryptography.
His work deals with themes such as Multimedia, Theoretical computer science, Steganography and Robustness, which intersect with Digital watermarking.
The Multimedia study combines topics in areas such as World Wide Web and Video processing.
His Watermark study combines topics from a wide range of disciplines, such as Digital image, Detector, Noise, Payload and Algorithm.
His Computer security study combines topics in areas such as Internet privacy and Identification.
His studies deal with areas such as Reliability, Computer vision and Pattern recognition as well as Artificial intelligence.
He most often published in these fields:
- Digital watermarking (48.65%)
- Watermark (26.35%)
- Computer security (19.59%)
What were the highlights of his more recent work (between 2007-2019)?
- Digital watermarking (48.65%)
- Speech recognition (10.14%)
- Artificial intelligence (20.95%)
In recent papers he was focusing on the following fields of study:
Ton Kalker mostly deals with Digital watermarking, Speech recognition, Artificial intelligence, Watermark and Robustness.
His Digital watermarking research includes elements of Theoretical computer science, Computer security, Cover, Cryptography and Steganography.
His Computer security research includes themes of Metadata, Side effect and Digital signature.
His work deals with themes such as PESQ, Reverberation and Impulse response, which intersect with Speech recognition.
His studies in Artificial intelligence integrate themes in fields like Probability distribution, Computer vision and Pattern recognition.
His work is dedicated to discovering how Watermark, Noise are connected with Encoding, Multiplexing, Lossy compression and Quantization and other disciplines.
Between 2007 and 2019, his most popular works were:
- Chapter 12 – Steganography (132 citations)
- Performance Analysis of a Block-Neighborhood-Based Self-Recovery Fragile Watermarking Scheme (55 citations)
- IEEE SIGNAL PROCESSING SOCIETY (46 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Algorithm
Ton Kalker mainly investigates Artificial intelligence, Robustness, Pattern recognition, Fingerprint recognition and Algorithm.
His study involves Feature extraction, Digital watermarking, Biometrics and Random projection, a branch of Artificial intelligence.
The Digital watermarking study combines topics in areas such as Theoretical computer science, Cover, Embedding, Steganography and Payload.
His Robustness research incorporates elements of Quantization, Speech recognition, Boosting, Statistical classification and Feature selection.
His Fingerprint recognition study integrates concerns from other disciplines, such as Detection theory, Detector and Fingerprint.
His Algorithm research is multidisciplinary, incorporating perspectives in Decomposition, Correlation and Speech processing.
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