What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Operating system
His primary areas of investigation include Artificial intelligence, Computer vision, Data compression, Multimedia and JPEG 2000.
His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning and Pattern recognition.
His study looks at the relationship between Computer vision and fields such as Distortion, as well as how they intersect with chemical problems.
The Data compression study combines topics in areas such as Visualization, Data mining, Human visual system model, Variable-length code and Signal compression.
His Multimedia research includes themes of Metadata, Quality of service, Quality of experience, Subjective video quality and Coding.
Touradj Ebrahimi interconnects JPEG, Transcoding, Quantization, Region of interest and Encryption in the investigation of issues within JPEG 2000.
His most cited work include:
- DEAP: A Database for Emotion Analysis ;Using Physiological Signals (1495 citations)
- The JPEG 2000 still image compression standard (1248 citations)
- The JPEG2000 still image coding system: an overview (1206 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Artificial intelligence, Computer vision, Multimedia, Data compression and Coding.
His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning and Pattern recognition.
His Computer vision research incorporates elements of Visualization, Video quality and Computer graphics.
His study explores the link between Multimedia and topics such as Quality of experience that cross with problems in Perception.
His Data compression research includes elements of Transform coding, Theoretical computer science and Computer engineering.
His Image compression research integrates issues from Image quality, JPEG and Wavelet transform.
He most often published in these fields:
- Artificial intelligence (53.31%)
- Computer vision (43.46%)
- Multimedia (19.19%)
What were the highlights of his more recent work (between 2015-2020)?
- Artificial intelligence (53.31%)
- Computer vision (43.46%)
- JPEG (10.36%)
In recent papers he was focusing on the following fields of study:
Artificial intelligence, Computer vision, JPEG, Point cloud and Image compression are his primary areas of study.
His studies deal with areas such as Machine learning and Pattern recognition as well as Artificial intelligence.
His work on Transform coding as part of general Computer vision study is frequently linked to Omnidirectional antenna, therefore connecting diverse disciplines of science.
His research integrates issues of Multimedia, Lossless compression, JPEG 2000, Standardization and Coding in his study of JPEG.
His Point cloud research incorporates themes from Visualization, Data mining, Representation and Ground truth.
He has included themes like Color depth and Transcoding in his Image compression study.
Between 2015 and 2020, his most popular works were:
- New Light Field Image Dataset (155 citations)
- JPEG Pleno: Toward an Efficient Representation of Visual Reality (97 citations)
- Food/Non-food Image Classification and Food Categorization using Pre-Trained GoogLeNet Model (70 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Operating system
His scientific interests lie mostly in Artificial intelligence, Computer vision, Visualization, Point cloud and JPEG.
His Artificial intelligence study integrates concerns from other disciplines, such as Field and Machine learning.
In the field of Computer vision, his study on Transform coding overlaps with subjects such as Dynamic web page.
His Visualization research is multidisciplinary, incorporating perspectives in Ground truth and Benchmark.
His JPEG study combines topics from a wide range of disciplines, such as Lossless compression, JPEG 2000, JPEG File Interchange Format, Standardization and Lossless JPEG.
The various areas that Touradj Ebrahimi examines in his Data compression study include Image quality and Volume.
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