Reza Hoseinnezhad

Professor Reza Hoseinnezhad

Professor
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Details

Open to

  • Masters Research or PhD student supervision

Supervisor projects

  • Development of a Machine Learning Based Algorithm for Characterising the Vehicle Interior Noise
  • 23 Sep 2024
  • Enhanced Collaborative Situational Awareness in Robotic Teaming through Multi-Object Tracking with Intermittent Communication
  • 4 Jun 2024
  • Information Fusion for Multi-Object Tracking in Large-Scale Sensor Network
  • 24 Nov 2023
  • Swarm Tracking in the Random Finite Set Framework
  • 20 Oct 2022
  • Fault Tolerant Control of Autonomous Underwater Vehicles
  • 14 Sep 2020
  • Statistical Information Fusion for Multi-Camera Visual Tracking
  • 18 Jun 2020
  • Stochastic Geometric Information Fusion for Cooperative Driving
  • 10 Dec 2019
  • Design and Control of a Miniature Structure-Climbing Robot
  • 1 Nov 2019
  • Tracking of Multiple Interacting Targets in the Random Finite Set Framework
  • 27 Mar 2019
  • Passive Visual Depth Estimation in the Deep Learning Era
  • 13 Dec 2018
  • In-Situ Monitoring of Laser Metal Deposition for Additive Manufacturing
  • 29 Oct 2018
  • Anomaly Detection in Machine Vision Applications
  • 1 Jun 2018
  • Identification of Moving Objects in Complex Dynamic Scenes Using Semantics
  • 1 Mar 2018
  • Intelligent Energy Management Control Systems for Autonomous Vehicles
  • 3 Jul 2017
  • Selective Sensor Control for Multi-Object Tracking
  • 18 Jul 2016
  • Multi - Object Tracking in Video using Labeled Random Finite Sets
  • 21 Jul 2014
  • Improved Image Analysis by Maximised Statistical Use of Geometry-Shape Constraints
  • 3 Mar 2014
  • Minimum Roll Control of an Autonomous Vehicles
  • 16 Jul 2012

Teaching interests

Range segmentation, Motion segmentation, Motion estimation, Visual tracking, Autonomous vehicles, sensor fusion, Drive-by-Wire, Multi-Target Tracking.

Research interests

Electrical and Electronic Engineering, Artificial Intelligence and Image Processing, Mechanical Engineering, Automotive Engineering, Manufacturing Engineering, Materials Engineering
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Acknowledgement of Country

RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business - Artwork 'Sentient' by Hollie Johnson, Gunaikurnai and Monero Ngarigo.

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