2026 David Suter: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	52	5109	4970	154	153	264	10291

David Suter publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where David Suter sits on this spectrum.

32 publications 991+

This scientist: 264 publications — 66th percentile

66% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

David Suter D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where David Suter sits on this spectrum.

30 D-Index 131+

This scientist: 52 D-Index — 65th percentile

65% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Research.com Recognitions

2023 - Research.com Computer Science in Australia Leader Award

Overview

David Suter is a researcher affiliated with Edith Cowan University in Australia. Their work spans multiple disciplines, primarily focusing on computer science, medicine, and engineering. The main fields of their research include computer vision and pattern recognition, artificial intelligence, biomedical engineering, and electrical and electronic engineering.

Their research covers a broad range of topics, with particular emphasis on advanced vision and imaging, advanced image and video retrieval techniques, bone health and osteoporosis research, machine learning and algorithms, advanced neural network applications, medical imaging and analysis, and robotics and sensor-based localization.

Key recent publications by David Suter include:

End-to-End Learning of Object Motion Estimation from Retinal Events for Event-Based Object Tracking (2020) published in Proceedings of the AAAI Conference on Artificial Intelligence
ITSA: An Information-Theoretic Approach to Automatic Shortcut Avoidance and Domain Generalization in Stereo Matching Networks (2022) published in 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Machine learning for abdominal aortic calcification assessment from bone density machine-derived lateral spine images (2023) published in EBioMedicine
A Hybrid Quantum-Classical Algorithm for Robust Fitting (2022) published in 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Motion Segmentation of RGB-D Sequences: Combining Semantic and Motion Information Using Statistical Inference (2020) published in IEEE Transactions on Image Processing

David Suter collaborates frequently with several co-authors, including:

Syed Zulqarnain Gilani
John T. Schousboe
William D. Leslie
Joshua R. Lewis
Ruwan Tennakoon

Their work has been published in numerous venues, with a significant number of papers appearing in:

arXiv (Cornell University)
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Journal of Bone and Mineral Research
IEEE Transactions on Pattern Analysis and Machine Intelligence
SSRN Electronic Journal

David Suter's multidisciplinary approach integrates advanced computational techniques within medical and engineering contexts. Their contributions involve both theoretical and applied research, emphasizing machine learning methodologies and imaging technologies across various domains.

Best Publications

As-Projective-As-Possible Image Stitching with Moving DLT

Unknown

757
Citations
As-Projective-As-Possible Image Stitching with Moving DLT

Julio Zaragoza;Tat-Jun Chin;Quoc-Huy Tran;Michael S. Brown

590
Citations
Fast Supervised Hashing with Decision Trees for High-Dimensional Data

Guosheng Lin;Chunhua Shen;Qinfeng Shi;Anton van den Hengel

466
Citations
Joint Detection and Estimation of Multiple Objects From Image Observations

Ba-Ngu Vo;Ba-Tuong Vo;Nam-Trung Pham;David Suter

446
Citations
Recognizing Human Activities from Silhouettes: Motion Subspace and Factorial Discriminative Graphical Model

Liang Wang;D. Suter

276
Citations
Adaptive Object Tracking Based on an Effective Appearance Filter

Hanzi Wang;D. Suter;K. Schindler;Chunhua Shen

237
Citations
Learning and Matching of Dynamic Shape Manifolds for Human Action Recognition

Liang Wang;D. Suter

231
Citations
Assessing the performance of corner detectors for point feature tracking applications

Prithiviraj Tissainayagam;David Suter

224
Citations
A consensus-based method for tracking: Modelling background scenario and foreground appearance

Hanzi Wang;David Suter

221
Citations
A General Two-Step Approach to Learning-Based Hashing

Guosheng Lin;Chunhua Shen;David Suter;Anton Van Den Hengel

213
Citations
Robust Optic Flow Computation

Alireza Bab-Hadiashar;David Suter

209
Citations
Incremental Kernel Principal Component Analysis

Tat-Jun Chin;D. Suter

205
Citations
Robust adaptive-scale parametric model estimation for computer vision

H. Wang;D. Suter

196
Citations
Visual tracking of numerous targets via multi-Bernoulli filtering of image data

Reza Hoseinnezhad;Ba-Ngu Vo;Ba-Tuong Vo;David Suter

195
Citations
Recovering the missing components in a large noisy low-rank matrix: application to SFM

P. Chen;D. Suter

192
Citations
Object tracking in image sequences using point features

P. Tissainayagam;D. Suter

166
Citations
Dynamic and hierarchical multi-structure geometric model fitting

Hoi Sim Wong;Tat-Jun Chin;Jin Yu;David Suter

166
Citations
3D terrestrial LIDAR classifications with super-voxels and multi-scale Conditional Random Fields

Ee Hui Lim;David Suter

154
Citations
Simultaneously Fitting and Segmenting Multiple-Structure Data with Outliers

Hanzi Wang;Tat-Jun Chin;D. Suter

141
Citations
Accelerated Hypothesis Generation for Multistructure Data via Preference Analysis

Tat-Jun Chin;Jin Yu;D. Suter

138
Citations
Robust fitting of multiple structures: The statistical learning approach

Tat-Jun Chin;Hanzi Wang;David Suter

136
Citations
The Random Cluster Model for robust geometric fitting

Trung Thanh Pham;Tat-Jun Chin;Jin Yu;David Suter

119
Citations

Frequent Co-Authors

Tat-Jun Chin University of Adelaide

Hanzi Wang Xiamen University

Alireza Bab-Hadiashar RMIT University

Konrad Schindler ETH Zurich

Yan Yan Zhejiang University

Reza Hoseinnezhad RMIT University

Chunhua Shen Zhejiang University

Anton van den Hengel University of Adelaide

Ba-Tuong Vo Curtin University

Ba-Ngu Vo Curtin University

External Links

Personal website of David Suter Google Scholar page

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

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