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Computer Science
Australia
2025

D-Index & Metrics

Computer Science

D-Index
68
Citations
24548
World Ranking
2046
National Ranking
63

Electronics and Electrical Engineering

D-Index
68
Citations
24936
World Ranking
989
National Ranking
36

Research.com Recognitions

  • 2025 - Research.com Computer Science in Australia Leader Award
  • 2023 - Research.com Computer Science in Australia Leader Award
  • 2022 - Research.com Computer Science in Australia Leader Award

Overview

Ba-Ngu Vo is affiliated with Curtin University in Australia and specializes in computer science with a focus on artificial intelligence, computer vision and pattern recognition, computer networks and communications, aerospace engineering, and signal processing. Their research contributions span multiple subfields, indicating a broad engagement with both theoretical and applied aspects of these areas.

Their main topics of work include:

  • Target Tracking and Data Fusion in Sensor Networks
  • Video Surveillance and Tracking Methods
  • Distributed Sensor Networks and Detection Algorithms
  • Fault Detection and Control Systems
  • Advanced Neural Network Applications
  • Adversarial Robustness in Machine Learning
  • Gaussian Processes and Bayesian Inference

Ba-Ngu Vo has published extensively in several notable venues, with the most frequent being:

  • IEEE Transactions on Signal Processing
  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Information Fusion
  • IEEE/ACM Transactions on Audio Speech and Language Processing

Some of their recent papers include:

  • "A Bayesian Filter for Multi-View 3D Multi-Object Tracking With Occlusion Handling" (2020), published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Distributed Multi-Object Tracking Under Limited Field of View Sensors" (2021), published in IEEE Transactions on Signal Processing
  • "Multi-Scan Multi-Sensor Multi-Object State Estimation" (2022), published in IEEE Transactions on Signal Processing
  • "How Trustworthy are Performance Evaluations for Basic Vision Tasks?" (2022), published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Linear Complexity Gibbs Sampling for Generalized Labeled Multi-Bernoulli Filtering" (2023), published in IEEE Transactions on Signal Processing

Their frequent co-authors include:

  • Ba-Tuong Vo
  • Tran Thien Dat Nguyen
  • Changbeom Shim
  • Hamid Rezatofighi
  • Jonah Ong

Ba-Ngu Vo's research reflects an integration of advanced techniques in multi-object tracking, probabilistic filtering, and sensor fusion, contributing to developments in surveillance, sensor networks, and machine learning systems. The portfolio of publication venues and collaborative network indicates consistent engagement with both the theoretical foundations and applied methodologies within their research fields.

Best Publications

  • The Gaussian Mixture Probability Hypothesis Density Filter

    Ba-Ngu Vo;Wing-Kin Ma

  • A Consistent Metric for Performance Evaluation of Multi-Object Filters

    D. Schuhmacher;B.-T. Vo;B.-N. Vo

  • Sequential Monte Carlo methods for multitarget filtering with random finite sets

    B.-N. Vo;S. Singh;A. Doucet

  • Analytic Implementations of the Cardinalized Probability Hypothesis Density Filter

    Ba-Tuong Vo;Ba-Ngu Vo;A. Cantoni

  • Labeled Random Finite Sets and Multi-Object Conjugate Priors

    Ba-Tuong Vo;Ba-Ngu Vo

  • The Cardinality Balanced Multi-Target Multi-Bernoulli Filter and Its Implementations

    Ba-Tuong Vo;Ba-Ngu Vo;A. Cantoni

  • The Labeled Multi-Bernoulli Filter

    Stephan Reuter;Ba-Tuong Vo;Ba-Ngu Vo;Klaus Dietmayer

  • Labeled Random Finite Sets and the Bayes Multi-Target Tracking Filter

    Ba-Ngu Vo;Ba-Tuong Vo;Dinh Phung

  • On performance evaluation of multi-object filters

    D. Schuhmacher;Ba Tuong Vo;Ba Ngu Vo

  • Sequential monte carlo implementation of the phd filter for multi-target tracking

    Ba-Ngu Vo;S. Singh;A. Doucet

  • Joint Detection and Estimation of Multiple Objects From Image Observations

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

  • An Efficient Implementation of the Generalized Labeled Multi-Bernoulli Filter

    Ba-Ngu Vo;Ba-Tuong Vo;Hung Gia Hoang

  • A Metric for Performance Evaluation of Multi-Target Tracking Algorithms

    B Ristic;Ba-Ngu Vo;D Clark;Ba-Tuong Vo

  • Adaptive Target Birth Intensity for PHD and CPHD Filters

    B. Ristic;D. Clark;Ba-Ngu Vo;Ba-Tuong Vo

  • A Random-Finite-Set Approach to Bayesian SLAM

    J Mullane;Ba-Ngu Vo;M D Adams;Ba-Tuong Vo

  • A Tutorial on Bernoulli Filters: Theory, Implementation and Applications

    B. Ristic;Ba-Tuong Vo;Ba-Ngu Vo;A. Farina

  • Data Association and Track Management for the Gaussian Mixture Probability Hypothesis Density Filter

    K. Panta;D.E. Clark;Ba-Ngu Vo

  • CPHD Filtering With Unknown Clutter Rate and Detection Profile

    R. P. S. Mahler;Ba-Tuong Vo;Ba-Ngu Vo

  • Tracking an unknown time-varying number of speakers using TDOA measurements: a random finite set approach

    Wing-Kin Ma;Ba-Ngu Vo;S.S. Singh;A. Baddeley

  • Multitarget Tracking

    Unknown

  • A Gaussian Mixture PHD Filter for Jump Markov System Models

    S.A. Pasha;Ba-Ngu Vo;Hoang Duong Tuan;Wing-Kin Ma

Frequent Co-Authors

Ba-Tuong Vo
Ba-Tuong Vo Curtin University
Antonio Cantoni
Antonio Cantoni University of Western Australia
Hoang Duong Tuan
Hoang Duong Tuan University of Technology Sydney
Arnaud Doucet
Arnaud Doucet University of Oxford
Wing-Kin Ma
Wing-Kin Ma Chinese University of Hong Kong
Branko Ristic
Branko Ristic RMIT University
Dinh Phung
Dinh Phung Monash University
Kok Lay Teo
Kok Lay Teo Sunway University
Reza Hoseinnezhad
Reza Hoseinnezhad RMIT University
Vikram Krishnamurthy
Vikram Krishnamurthy Cornell University

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