D-Index & Metrics Best Publications

D-Index & Metrics

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 32 Citations 6,810 117 World Ranking 7396 National Ranking 358

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Algorithm
  • Computer vision

His main research concerns Artificial intelligence, Computer vision, Pattern recognition, Algorithm and Shape analysis. His is involved in several facets of Artificial intelligence study, as is seen by his studies on Iterative reconstruction, Noise, Pixel, Rendering and Benchmark. His Computer vision research includes themes of Computer graphics and Outlier.

His work in Pattern recognition addresses subjects such as Artificial neural network, which are connected to disciplines such as Feature, Histogram and Deep learning. His research in the fields of Reduction overlaps with other disciplines such as Redundancy. His work in Shape analysis tackles topics such as Computer graphics which are related to areas like Theoretical computer science.

His most cited work include:

  • Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks (810 citations)
  • Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis (319 citations)
  • Pattern-aware Deformation Using Sliding Dockers (240 citations)

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

Michael Wand mainly investigates Artificial intelligence, Speech recognition, Algorithm, Computer vision and Computer graphics. His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning and Pattern recognition. His work on Feature extraction as part of general Pattern recognition research is often related to Texture synthesis, thus linking different fields of science.

His work in the fields of Algorithm, such as Matching, overlaps with other areas such as Markov random field. Many of his research projects under Rendering are closely connected to Data structure with Data structure, tying the diverse disciplines of science together. Artificial neural network connects with themes related to Feature in his study.

He most often published in these fields:

  • Artificial intelligence (33.54%)
  • Speech recognition (29.81%)
  • Algorithm (21.74%)

What were the highlights of his more recent work (between 2016-2021)?

  • Speech recognition (29.81%)
  • Artificial intelligence (33.54%)
  • Artificial neural network (8.07%)

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

The scientist’s investigation covers issues in Speech recognition, Artificial intelligence, Artificial neural network, Training and Phase. His work deals with themes such as Motion and Word, which intersect with Speech recognition. His Artificial intelligence study incorporates themes from Machine learning, Inverse problem and Computer vision.

He has researched Artificial neural network in several fields, including Test, Structure, Muscle activity and Algorithm. He interconnects Sampling, Convolution and Adaptive control in the investigation of issues within Algorithm. His work carried out in the field of Phase brings together such families of science as Boltzmann distribution, Energy minimization and Molecular dynamics.

Between 2016 and 2021, his most popular works were:

  • Biosignal-Based Spoken Communication: A Survey (74 citations)
  • Benchmarking non-photorealistic rendering of portraits (14 citations)
  • Domain-Adversarial Training for Session Independent EMG-based Speech Recognition. (13 citations)

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

  • Artificial intelligence
  • Machine learning
  • Algorithm

His primary scientific interests are in Speech recognition, Training, Domain, Adversarial system and Independence. His Speech recognition research includes elements of Artificial neural network, End-to-end principle and Noise. In his work, Michael Wand performs multidisciplinary research in Training and Session.

His work deals with themes such as Accuracy improvement and Recurrent neural network, which intersect with Independence.

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

Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks

Chuan Li;Michael Wand.
european conference on computer vision (2016)

942 Citations

Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis

Chuan Li;Michael Wand.
computer vision and pattern recognition (2016)

399 Citations

Interactive rendering of large volume data sets

S. Guthe;M. Wand;J. Gonser;W. Strasser.
ieee visualization (2002)

339 Citations

Pattern-aware Deformation Using Sliding Dockers

Martin Bokeloh;Michael Wand;Vladlen Koltun;Hans-Peter Seidel.
international conference on computer graphics and interactive techniques (2011)

313 Citations

Symmetry in 3D Geometry: Extraction and Applications

Niloy J. Mitra;Mark Pauly;Michael Wand;Duygu Ceylan.
eurographics (2013)

290 Citations

Structure-aware shape processing

Niloy J. Mitra;Michael Wand;Hao Zhang;Daniel Cohen-Or.
international conference on computer graphics and interactive techniques (2013)

223 Citations

A connection between partial symmetry and inverse procedural modeling

Martin Bokeloh;Michael Wand;Hans-Peter Seidel.
international conference on computer graphics and interactive techniques (2010)

213 Citations

The randomized z-buffer algorithm: interactive rendering of highly complex scenes

Michael Wand;Matthias Fischer;Ingmar Peter;Friedhelm Meyer auf der Heide.
international conference on computer graphics and interactive techniques (2001)

207 Citations

Optimal HDR reconstruction with linear digital cameras

Miguel Granados;Boris Ajdin;Michael Wand;Christian Theobalt.
computer vision and pattern recognition (2010)

182 Citations

Modeling coarticulation in EMG-based continuous speech recognition

Tanja Schultz;Michael Wand.
Speech Communication (2010)

178 Citations

Best Scientists Citing Michael Wand

Hao Zhang

Hao Zhang

Simon Fraser University

Publications: 55

Leonidas J. Guibas

Leonidas J. Guibas

Stanford University

Publications: 51

Niloy J. Mitra

Niloy J. Mitra

University College London

Publications: 45

Peter Wonka

Peter Wonka

King Abdullah University of Science and Technology

Publications: 41

Kai Xu

Kai Xu

National University of Defense Technology

Publications: 38

Tanja Schultz

Tanja Schultz

University of Bremen

Publications: 37

Daniel Cohen-Or

Daniel Cohen-Or

Tel Aviv University

Publications: 37

Christian Theobalt

Christian Theobalt

Max Planck Institute for Informatics

Publications: 32

Hans-Peter Seidel

Hans-Peter Seidel

Max Planck Institute for Informatics

Publications: 29

Michael M. Bronstein

Michael M. Bronstein

Imperial College London

Publications: 28

Alexander M. Bronstein

Alexander M. Bronstein

Technion – Israel Institute of Technology

Publications: 27

Yu-Kun Lai

Yu-Kun Lai

Cardiff University

Publications: 27

Maks Ovsjanikov

Maks Ovsjanikov

École Polytechnique

Publications: 25

Hao Li

Hao Li

University of California, Berkeley

Publications: 22

Eli Shechtman

Eli Shechtman

Adobe Systems (United States)

Publications: 21

Daniel G. Aliaga

Daniel G. Aliaga

Purdue University West Lafayette

Publications: 21

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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