World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
12899
World Ranking
6065
National Ranking
2734

Overview

Thomas Deselaers is a researcher affiliated with Apple (United States) focusing on areas within computer science. Their work spans multiple subfields including computer vision and pattern recognition, artificial intelligence, computer graphics and computer-aided design, signal processing, and computational mechanics.

The research topics covered by Thomas Deselaers include:

  • Handwritten Text Recognition Techniques
  • Natural Language Processing Techniques
  • Image Processing and 3D Reconstruction
  • Computer Graphics and Visualization Techniques
  • Music and Audio Processing
  • 3D Shape Modeling and Analysis
  • Human Motion and Animation

Thomas Deselaers has contributed to various scholarly publications, with papers appearing primarily in computer science venues. Their recent papers include:

  • Fast multi-language LSTM-based online handwriting recognition, 2020, International Journal on Document Analysis and Recognition (IJDAR)
  • CoSE: Compositional Stroke Embeddings, 2020, arXiv (Cornell University)
  • The DIDI dataset: Digital Ink Diagram data, 2020, arXiv (Cornell University)
  • CoSE: Compositional Stroke Embeddings, 2021, Repository for Publications and Research Data (ETH Zurich)
  • Data Incubation - Synthesizing Missing Data for Handwriting Recognition, 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

The frequent co-authors collaborating with Thomas Deselaers consist of:

  • Emre Aksan
  • Otmar Hilliges
  • Philippe Gervais
  • Andrea Tagliasacchi
  • Jen-Hao Rick Chang

Thomas Deselaers publishes regularly in the following venues:

  • arXiv (Cornell University)
  • International Journal on Document Analysis and Recognition (IJDAR)
  • Repository for Publications and Research Data (ETH Zurich)
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Their specialization in handwritten text recognition techniques is reflected in the majority of their publications, often involving novel approaches to online handwriting recognition and digital ink analysis. Their work extends into synthesis of data for recognition improvement and embedding techniques for compositional stroke analysis, overlapping with other areas such as natural language processing and computer vision.

Best Publications

  • Measuring the Objectness of Image Windows

    B. Alexe;T. Deselaers;V. Ferrari

  • What is an object

    Bogdan Alexe;Thomas Deselaers;Vittorio Ferrari

  • ClassCut for unsupervised class segmentation

    Bogdan Alexe;Thomas Deselaers;Vittorio Ferrari

  • Features for image retrieval: an experimental comparison

    Thomas Deselaers;Daniel Keysers;Hermann Ney

  • The 2005 PASCAL visual object classes challenge

    Mark Everingham;Andrew Zisserman;Christopher K. I. Williams;Luc Van Gool

  • Weakly Supervised Localization and Learning with Generic Knowledge

    Thomas Deselaers;Bogdan Alexe;Vittorio Ferrari

  • Deformation Models for Image Recognition

    D. Keysers;T. Deselaers;C. Gollan;H. Ney

  • Automatic categorization of medical images for content-based retrieval and data mining.

    Thomas M. Lehmann;Mark O. Güld;Thomas Deselaers;Daniel Keysers

  • The CLEF 2005 cross–language image retrieval track

    Paul Clough;Henning Müller;Thomas Deselaers;Michael Grubinger

  • Bag-of-visual-words models for adult image classification and filtering

    T. Deselaers;L. Pimenidis;H. Ney

  • Overview of the ImageCLEFmed 2006 medical retrieval and medical annotation tasks

    Henning Müller;Thomas Deselaers;Thomas Deserno;Paul Clough

  • Localizing objects while learning their appearance

    Thomas Deselaers;Bogdan Alexe;Vittorio Ferrari

  • ImageCLEF: Experimental Evaluation in Visual Information Retrieval

    Henning Mller;Paul Clough;Thomas Deselaers;Barbara Caputo

  • Features for Image Retrieval: A Quantitative Comparison

    Thomas Deselaers;Daniel Keysers;Hermann Ney

  • Multi-Language Online Handwriting Recognition

    Daniel Keysers;Thomas Deselaers;Henry A. Rowley;Li-Lun Wang

  • Visual and semantic similarity in ImageNet

    Thomas Deselaers;Vittorio Ferrari

  • Speech recognition techniques for a sign language recognition system.

    Philippe Dreuw;David Rybach;Thomas Deselaers;Morteza Zahedi

  • Discriminative training for object recognition using image patches

    T. Deselaers;D. Keysers;H. Ney

  • A Deep Learning Approach to Machine Transliteration

    Thomas Deselaers;Saša Hasan;Oliver Bender;Hermann Ney

  • Evaluating Systems for Multilingual and Multimodal Information Access

    Carol Peters;Thomas Deselaers;Nicola Ferro;Julio Gonzalo

  • The CLEF 2004 cross-language image retrieval track

    Paul Clough;Henning Müller;Mark Sanderson

  • Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on

    T. Deselaers;Vittorio Ferrari

Frequent Co-Authors

Daniel Keysers
Daniel Keysers Google (United States)
Hermann Ney
Hermann Ney RWTH Aachen University
Henning Müller
Henning Müller University of Applied Sciences and Arts Western Switzerland
Henry Allan Rowley
Henry Allan Rowley Google (United States)
Vittorio Ferrari
Vittorio Ferrari Google (United States)
Paul Clough
Paul Clough University of Sheffield
William R. Hersh
William R. Hersh Oregon Health & Science University
Georg Heigold
Georg Heigold German Research Centre for Artificial Intelligence
Enrique Vidal
Enrique Vidal Universitat Politècnica de València

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring computer science in the USA opens doors to various easy degrees to get online that pay well. Many students prefer online study for its flexibility and affordability, with several reputable programs offering accelerated or specialized tracks.

For those seeking management roles within the tech sector, online MBA programs are an excellent way to gain business expertise while continuing to work or study in computer science. Alternatively, individuals can consider the fastest route to advanced qualifications through online masters—many one-year programs now focus on tech and related fields.

As artificial intelligence skills are in high demand, earning a credential from one of the best online ai degree programs can further boost your career prospects. These online degrees help you develop skills that employers are searching for, all while saving on costs and gaining flexibility in your study schedule.

Best Scientists Citing Thomas Deselaers

Trending Scientists