D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 40 Citations 12,155 336 World Ranking 5634 National Ranking 263

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Algorithm

His main research concerns Artificial intelligence, Computer vision, Multimedia, Video tracking and Pattern recognition. His study in Image segmentation, Motion compensation, Image processing, Feature extraction and Discrete cosine transform is carried out as part of his studies in Artificial intelligence. His research combines Algorithm and Computer vision.

His Multimedia research incorporates elements of MPEG-4, Uncompressed video, Digital television, Data compression and Interoperability. His work deals with themes such as Computational complexity theory and Radar tracker, which intersect with Video tracking. Thomas Sikora usually deals with Pattern recognition and limits it to topics linked to Speech recognition and Mel-frequency cepstrum, Audio frequency and Matrix.

His most cited work include:

  • Introduction to MPEG-7: Multimedia Content Description Interface (1036 citations)
  • Overview of the MPEG-7 standard (589 citations)
  • The MPEG-4 video standard verification model (577 citations)

What are the main themes of his work throughout his whole career to date?

Thomas Sikora spends much of his time researching Artificial intelligence, Computer vision, Pattern recognition, Motion estimation and Segmentation. Motion compensation, Feature extraction, Image segmentation, Pixel and Image processing are among the areas of Artificial intelligence where Thomas Sikora concentrates his study. His research on Computer vision often connects related topics like Algorithm.

His study looks at the relationship between Pattern recognition and topics such as Speech recognition, which overlap with Mel-frequency cepstrum. The various areas that Thomas Sikora examines in his Segmentation study include Object and Iterative reconstruction. His Data compression research includes themes of Transform coding and Multimedia.

He most often published in these fields:

  • Artificial intelligence (71.30%)
  • Computer vision (52.66%)
  • Pattern recognition (18.64%)

What were the highlights of his more recent work (between 2012-2020)?

  • Artificial intelligence (71.30%)
  • Computer vision (52.66%)
  • Pattern recognition (18.64%)

In recent papers he was focusing on the following fields of study:

Thomas Sikora mainly investigates Artificial intelligence, Computer vision, Pattern recognition, Motion estimation and Video tracking. His Artificial intelligence study frequently intersects with other fields, such as Machine learning. His research in Computer vision focuses on subjects like Detector, which are connected to Tracking and Scheme.

His research integrates issues of Transform coding, Data compression, Iterative reconstruction and Kernel in his study of Pattern recognition. His studies deal with areas such as Computational complexity theory, Information privacy, Search engine indexing and Automatic summarization as well as Video tracking. His Quarter-pixel motion study which covers Block-matching algorithm that intersects with Motion vector.

Between 2012 and 2020, his most popular works were:

  • High-Speed tracking-by-detection without using image information (158 citations)
  • Sequential sensor fusion combining probability hypothesis density and kernelized correlation filters for multi-object tracking in video data (53 citations)
  • Extending IOU Based Multi-Object Tracking by Visual Information (52 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Computer vision
  • Machine learning

His scientific interests lie mostly in Artificial intelligence, Computer vision, Machine learning, Object detection and Feature. In his study, which falls under the umbrella issue of Artificial intelligence, Transform coding is strongly linked to Pattern recognition. His study looks at the relationship between Computer vision and topics such as Detector, which overlap with Process.

His Machine learning research includes elements of Estimation, Set and Global Positioning System. His Feature study also includes

  • Probabilistic logic and Field most often made with reference to Density estimation,
  • Motion which intersects with area such as Representation. As part of the same scientific family, Thomas Sikora usually focuses on Stereoscopy, concentrating on Depth map and intersecting with Image processing.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Introduction to MPEG-7: Multimedia Content Description Interface

Phillipe Salembier;Thomas Sikora;B.S. Manjunath.
(2002)

2202 Citations

The MPEG-4 video standard verification model

T. Sikora.
IEEE Transactions on Circuits and Systems for Video Technology (1997)

951 Citations

The MPEG-7 visual standard for content description-an overview

T. Sikora.
IEEE Transactions on Circuits and Systems for Video Technology (2001)

789 Citations

Overview of the MPEG-7 standard

Shih-Fu Chang;T. Sikora;A. Purl.
IEEE Transactions on Circuits and Systems for Video Technology (2001)

717 Citations

MPEG digital video-coding standards

T. Sikora.
IEEE Signal Processing Magazine (1997)

571 Citations

High-Speed tracking-by-detection without using image information

Erik Bochinski;Volker Eiselein;Thomas Sikora.
advanced video and signal based surveillance (2017)

407 Citations

MPEG-7 Audio and Beyond: Audio Content Indexing and Retrieval

Hyoung-Gook Kim;Nicolas Moreau;Thomas Sikora.
(2005)

402 Citations

Shape-adaptive DCT for generic coding of video

T. Sikora;B. Makai.
IEEE Transactions on Circuits and Systems for Video Technology (1995)

392 Citations

Trends and Perspectives in Image and Video Coding

T. Sikora.
Proceedings of the IEEE (2005)

315 Citations

3D Videocommunication: Algorithms, concepts and real-time systems in human centred communication

Oliver Schreer;Peter Kauff;Thomas Sikora.
No Category (2005)

232 Citations

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