What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Computer vision
His primary areas of investigation include Artificial intelligence, Digital watermarking, Computer vision, Watermark and Image processing.
His Artificial intelligence study combines topics in areas such as Algorithm and Machine learning.
His Digital watermarking research is multidisciplinary, relying on both Computer security, Multimedia, Steganography and Fidelity.
Ingemar J. Cox interconnects Dither and Copy protection in the investigation of issues within Multimedia.
His Computer vision research includes elements of Autonomous system, Mobile robot navigation and Autonomous robot, Mobile robot.
His Watermark research incorporates themes from Lossy compression, Spread spectrum, Signal, Data compression and Distortion.
His most cited work include:
- Secure spread spectrum watermarking for multimedia (5450 citations)
- Digital Watermarking (2714 citations)
- Digital Watermarking and Steganography (1323 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Artificial intelligence, Digital watermarking, Computer vision, Watermark and Information retrieval.
His Artificial intelligence research includes themes of Machine learning and Pattern recognition.
His study on Digital watermarking also encompasses disciplines like
- Computer security and related Digital Watermarking Alliance,
- Steganography, which have a strong connection to Information hiding.
His primary area of study in Computer vision is in the field of Rotation.
Ingemar J. Cox has included themes like Signal, Coding, Robustness and Discrete cosine transform in his Watermark study.
His study focuses on the intersection of Information retrieval and fields such as Relevance feedback with connections in the field of Bayesian probability.
He most often published in these fields:
- Artificial intelligence (39.11%)
- Digital watermarking (24.02%)
- Computer vision (18.16%)
What were the highlights of his more recent work (between 2013-2021)?
- Artificial intelligence (39.11%)
- Machine learning (12.29%)
- Action (4.47%)
In recent papers he was focusing on the following fields of study:
Ingemar J. Cox spends much of his time researching Artificial intelligence, Machine learning, Action, Social media and Information retrieval.
His study on Artificial intelligence is mostly dedicated to connecting different topics, such as Pattern recognition.
His biological study spans a wide range of topics, including Key, Task and Online search.
His study explores the link between Information retrieval and topics such as Electronic media that cross with problems in Event.
His study looks at the relationship between Identifier and fields such as Upload, as well as how they intersect with chemical problems.
His work carried out in the field of Feature vector brings together such families of science as Nearest neighbor search, Selection and Computer vision.
Between 2013 and 2021, his most popular works were:
- Digital technologies in the public-health response to COVID-19. (84 citations)
- Digital technologies in the public-health response to COVID-19. (84 citations)
- Detecting Disease Outbreaks in Mass Gatherings Using Internet Data (51 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Machine learning
His primary scientific interests are in Artificial intelligence, Machine learning, Online search, Transfer of learning and News media.
He studies Artificial intelligence, namely Supervised learning.
The various areas that he examines in his Machine learning study include Inference and Data mining.
His studies deal with areas such as Overfitting, Identification, Feature vector, Spurious relationship and Feature selection as well as Inference.
The concepts of his Data mining study are interwoven with issues in Quality, Learning to rank, Key and Semantic interpretation.
His Task research incorporates elements of Binary classification, Classifier, Set and Kernel.
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