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Computer Science
Australia
2023

D-Index & Metrics

Computer Science

D-Index
52
Citations
10291
World Ranking
5108
National Ranking
153

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

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

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

  • Fast Supervised Hashing with Decision Trees for High-Dimensional Data

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

  • Joint Detection and Estimation of Multiple Objects From Image Observations

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

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

    Liang Wang;D. Suter

  • Adaptive Object Tracking Based on an Effective Appearance Filter

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

  • Learning and Matching of Dynamic Shape Manifolds for Human Action Recognition

    Liang Wang;D. Suter

  • Assessing the performance of corner detectors for point feature tracking applications

    Prithiviraj Tissainayagam;David Suter

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

    Hanzi Wang;David Suter

  • A General Two-Step Approach to Learning-Based Hashing

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

  • Robust Optic Flow Computation

    Alireza Bab-Hadiashar;David Suter

  • Incremental Kernel Principal Component Analysis

    Tat-Jun Chin;D. Suter

  • Robust adaptive-scale parametric model estimation for computer vision

    H. Wang;D. Suter

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

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

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

    P. Chen;D. Suter

  • Object tracking in image sequences using point features

    P. Tissainayagam;D. Suter

  • Dynamic and hierarchical multi-structure geometric model fitting

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

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

    Ee Hui Lim;David Suter

  • Simultaneously Fitting and Segmenting Multiple-Structure Data with Outliers

    Hanzi Wang;Tat-Jun Chin;D. Suter

  • Accelerated Hypothesis Generation for Multistructure Data via Preference Analysis

    Tat-Jun Chin;Jin Yu;D. Suter

  • Robust fitting of multiple structures: The statistical learning approach

    Tat-Jun Chin;Hanzi Wang;David Suter

  • The Random Cluster Model for robust geometric fitting

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

Frequent Co-Authors

Tat-Jun Chin
Tat-Jun Chin University of Adelaide
Hanzi Wang
Hanzi Wang Xiamen University
Alireza Bab-Hadiashar
Alireza Bab-Hadiashar RMIT University
Reza Hoseinnezhad
Reza Hoseinnezhad RMIT University
Chunhua Shen
Chunhua Shen Zhejiang University
Anton van den Hengel
Anton van den Hengel University of Adelaide
Ba-Tuong Vo
Ba-Tuong Vo Curtin University
Guosheng Lin
Guosheng Lin Nanyang Technological University
Ba-Ngu Vo
Ba-Ngu Vo Curtin University

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