What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Algorithm
Matthew L. Miller mostly deals with Digital watermarking, Artificial intelligence, Computer vision, Watermark and Image processing.
Matthew L. Miller does research in Digital watermarking, focusing on Digital Watermarking Alliance specifically.
His Digital Watermarking Alliance study integrates concerns from other disciplines, such as Field and Key.
His work in Artificial intelligence covers topics such as Machine learning which are related to areas like Bayesian inference.
In general Computer vision, his work in Articulated body pose estimation, 3D pose estimation and Pose is often linked to Function linking many areas of study.
His studies in Watermark integrate themes in fields like Lossy compression and Rotation.
His most cited work include:
- Digital Watermarking (2714 citations)
- Digital Watermarking and Steganography (1323 citations)
- The Bayesian image retrieval system, PicHunter: theory, implementation, and psychophysical experiments (693 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Digital watermarking, Watermark, Artificial intelligence, Computer vision and Algorithm.
His Digital watermarking research includes themes of Computer security, Theoretical computer science, Steganography and Robustness.
His work deals with themes such as Variety and Digital Watermarking Alliance, which intersect with Computer security.
Matthew L. Miller has researched Watermark in several fields, including Decoding methods, Coding, Discrete cosine transform and Signal.
His Artificial intelligence research includes elements of Detector and Pattern recognition.
When carried out as part of a general Algorithm research project, his work on Code word is frequently linked to work in Gaussian, Set and Measure, therefore connecting diverse disciplines of study.
He most often published in these fields:
- Digital watermarking (43.65%)
- Watermark (39.68%)
- Artificial intelligence (37.30%)
What were the highlights of his more recent work (between 2006-2020)?
- Digital watermarking (43.65%)
- Watermark (39.68%)
- Artificial intelligence (37.30%)
In recent papers he was focusing on the following fields of study:
Matthew L. Miller focuses on Digital watermarking, Watermark, Artificial intelligence, Steganography and RF power amplifier.
Matthew L. Miller interconnects Theoretical computer science, Computer security, Cover, Embedding and Algorithm in the investigation of issues within Digital watermarking.
He has included themes like False positive paradox, Data mining, Noise, Robustness and Checksum in his Watermark study.
Matthew L. Miller combines subjects such as Detector, Computer vision and Pattern recognition with his study of Artificial intelligence.
His work on Steganalysis as part of general Steganography study is frequently linked to Property and Benchmarking, therefore connecting diverse disciplines of science.
His work carried out in the field of Steganalysis brings together such families of science as Digital audio, Steganography tools and Digital Watermarking Alliance.
Between 2006 and 2020, his most popular works were:
- Digital Watermarking and Steganography (1323 citations)
- Synergistic Face Detection and Pose Estimation with Energy-Based Models (273 citations)
- Chapter 12 – Steganography (132 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Algorithm
Matthew L. Miller mainly investigates Artificial intelligence, Computer vision, Detector, Convolutional neural network and Steganography.
Matthew L. Miller conducts interdisciplinary study in the fields of Artificial intelligence and Context through his research.
In general Computer vision study, his work on Digital image and Color image often relates to the realm of Biopsy and Automated method, thereby connecting several areas of interest.
His research on Detector frequently links to adjacent areas such as Pixel.
The concepts of his Steganography study are interwoven with issues in Computer security, Luby transform code and Digital Watermarking Alliance, Digital watermarking.
His work deals with themes such as Digital audio, Theoretical computer science and Steganalysis, which intersect with Digital watermarking.
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