ORCID Profile
0000-0001-9525-1467
Current Organisation
RMIT University
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Computer Vision | Stochastic Analysis and Modelling | Signal Processing | Manufacturing Robotics and Mechatronics (excl. Automotive Mechatronics) | Statistics | Artificial Intelligence and Image Processing | Calculus of Variations, Systems Theory and Control Theory | Manufacturing Engineering | Manufacturing Processes and Technologies (excl. Textiles) | Electrical and Electronic Engineering | Cell Development, Proliferation and Death | Image Processing
ANZSRC Socio-Economic Objective (SEO)
Industrial Instruments | Integrated Systems | Expanding Knowledge in the Mathematical Sciences | Automotive Equipment | Sheet Metal Products | Emerging Defence Technologies | Expanding Knowledge in Engineering | Expanding Knowledge in the Biological Sciences | National Security | Road Passenger Movements (excl. Public Transport) |
Related Links
Publications
MCMC based sampling technique for robust multi-model fitting and visual data segmentation
Publisher: IEEE
Date: 12-2016
Welcome from the Conference Chairs
Publisher: IEEE
Date: 10-2015
Multi-bernoulli sensor control for multi-target tracking
Publisher: IEEE
Date: 04-2013
Multi-sensor control for multi-object Bayes filters
Publisher: Elsevier BV
Date: 2018
A novel hybrid angle tracking observer for resolver to digital conversion
Publisher: IEEE
Date: 2005
Joint estimation of location and signal parameters for an LFM emitter
Publisher: Elsevier BV
Date: 05-2017
Deep learning for texture classification via multi-wavelet fusion of scattering transforms
Publisher: IEEE
Date: 02-2017
Computationally Efficient Distributed Multi-Sensor Fusion With Multi-Bernoulli Filter
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
On-Line Visual Tracking with Occlusion Handling
Publisher: MDPI AG
Date: 10-02-2020
DOI: 10.3390/S20030929
Abstract: One of the core challenges in visual multi-target tracking is occlusion. This is especially important in applications such as video surveillance and sports analytics. While offline batch processing algorithms can utilise future measurements to handle occlusion effectively, online algorithms have to rely on current and past measurements only. As such, it is markedly more challenging to handle occlusion in online applications. To address this problem, we propagate information over time in a way that it generates a sense of déjà vu when similar visual and motion features are observed. To achieve this, we extend the Generalized Labeled Multi-Bernoulli (GLMB) filter, originally designed for tracking point-sized targets, to be used in visual multi-target tracking. The proposed algorithm includes a novel false alarm detection/removal and label recovery methods capable of reliably recovering tracks that are even lost for a substantial period of time. We compare the performance of the proposed method with the state-of-the-art methods in challenging datasets using standard visual tracking metrics. Our comparisons show that the proposed method performs favourably compared to the state-of-the-art methods, particularly in terms of ID switches and fragmentation metrics which signifies occlusion.
Bridging parameter and data spaces for fast robust estimation in computer vision
Publisher: IEEE
Date: 2008
Non-Bayesian Track-Before-Detect Using Cauchy-Schwarz Divergence-Based Information Fusion
Publisher: IEEE
Date: 07-2018
Low insertion loss and high isolation capacitive RF MEMS switch with low pull-in voltage
Publisher: Springer Science and Business Media LLC
Date: 24-05-2017
Pseudo information measure: A new concept for extension of Bayesian fusion in robotic map building
Publisher: Elsevier BV
Date: 03-2002
Random Finite Set-Based Anomaly Detection for Safety Monitoring in Construction Sites
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Retinal fluid segmentation in OCT images using adversarial loss based convolutional neural networks
Publisher: IEEE
Date: 04-2018
Pulse discrimination for electrical discharge machining with rotating electrode
Publisher: Informa UK Limited
Date: 04-2013
3D registration in dark environments using RGB-D cameras
Publisher: IEEE
Date: 11-2013
Robust Object Classification Approach Using Spherical Harmonics
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
A multi objective fuzzy-based controller for front differential vehicles by electrical traction system on non-driven wheels
Publisher: IEEE
Date: 10-2008
Design and adaptive control of a kinematically redundant robot with enhanced trajectory tracking for climbing in tight spaces
Publisher: Elsevier BV
Date: 11-2022
Statistical analysis of three-dimensional optical flow separability in volumetric images
Publisher: Institution of Engineering and Technology (IET)
Date: 12-2015
State Transition for Statistical SLAM Using Planar Features in 3D Point Clouds
Publisher: MDPI AG
Date: 03-04-2019
DOI: 10.3390/S19071614
Abstract: There is a large body of literature on solving the SLAM problem for various autonomous vehicle applications. A substantial part of the solutions is formulated based on using statistical (mainly Bayesian) filters such as Kalman filter and its extended version. In such solutions, the measurements are commonly some point features or detections collected by the sensor(s) on board the autonomous vehicle. With the increasing utilization of scanners with common autonomous cars, and availability of 3D point clouds in real-time and at fast rates, it is now possible to use more sophisticated features extracted from the point clouds for filtering. This paper presents the idea of using planar features with multi-object Bayesian filters for SLAM. With Bayesian filters, the first step is prediction, where the object states are propagated to the next time based on a stochastic transition model. We first present how such a transition model can be developed, and then propose a solution for state prediction. In the simulation studies, using a dataset of measurements acquired from real vehicle sensors, we apply the proposed model to predict the next planar features and vehicle states. The results show reasonable accuracy and efficiency for statistical filtering-based SLAM applications.
Deep Learning-Based Incorporation of Planar Constraints for Robust Stereo Depth Estimation in Autonomous Vehicle Applications
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2022
Cooperative sensor fusion in centralized sensor networks using Cauchy–Schwarz divergence
Publisher: Elsevier BV
Date: 02-2020
Analysis of forklift accident trends within Victorian industry (Australia)
Publisher: Elsevier BV
Date: 12-2013
Recent patents on measurement and estimation in brake-by-wire technology
Publisher: Bentham Science Publishers Ltd.
Date: 2009
Accelerated Multi-Sensor Control for Selective Multi-Object Tracking
Publisher: IEEE
Date: 10-2018
Improved pose estimation for mobile robots by fusion of odometry data and environment map
Publisher: Springer Science and Business Media LLC
Date: 2003
Robust Distributed Fusion With Labeled Random Finite Sets
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-01-2018
Motion Segmentation of RGB-D Sequences: Combining Semantic and Motion Information Using Statistical Inference
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Occlusion handling for online visual tracking using labeled random set filters
Publisher: IEEE
Date: 10-2017
Gap width control in electrical discharge machining, using type-2 fuzzy controllers
Publisher: IEEE
Date: 11-2013
Classification of Volumetric Images Using Multi-Instance Learning and Extreme Value Theorem
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2019
Conditions for motion-background segmentation using fundamental matrix
Publisher: Institution of Engineering and Technology (IET)
Date: 2009
Emitter localization based on signal waveform estimation
Publisher: IEEE
Date: 05-2017
Conditions for segmentation of 2D translations of 3D objects
Publisher: Springer Berlin Heidelberg
Date: 2009
An M-estimator for high breakdown robust estimation in computer vision
Publisher: Elsevier BV
Date: 08-2011
Statistical separability of local motions in volumetric images
Publisher: IEEE
Date: 09-2013
Study on application of interval type 2 fuzzy logic control for gap width controller used in EDM machine
Publisher: Trans Tech Publications, Ltd.
Date: 08-2013
DOI: 10.4028/WWW.SCIENTIFIC.NET/AMM.365-366.863
Abstract: This paper presents a new method for controlling the gap distance in an EDM machine. Existing gap width control method using PI controller does not perform efficiently in a highly nonlinear and time-variant process such as EDM. In this method, constant tuning of the PI controller is required to achieve a stable and efficient EDM process. The new gap control method present in this paper uses an artificial intelligent type 2 fuzzy logic control to control the gap distance between the electrode and the workpiece. The main advantage of this proposed method is its robustness that would rid the practitioners from the tedious tuning job and would provide the industry with better accuracy and confidence in the control performance.
Direct yaw moment control for electric and hybrid vehicles with independent motors
Publisher: Inderscience Publishers
Date: 2015
Effective Sampling: Fast Segmentation Using Robust Geometric Model Fitting
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2018
An Information-Theoretic Method to Automatic Shortcut Avoidance and Domain Generalization for Dense Prediction Tasks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2023
A survey of control methods for electrical discharge machining process
Publisher: Bentham Science Publishers Ltd.
Date: 03-2013
OSPA-based sensor control
Publisher: IEEE
Date: 10-2015
Sensor-Management for Multitarget Filters via Minimization of Posterior Dispersion
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2017
Multi-object filtering from image sequence without detection
Publisher: IEEE
Date: 2010
Robust Model Fitting Using Higher Than Minimal Subset Sampling
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2016
A novel adaptive sliding mode control approach for electric vehicle direct yaw-moment control
Publisher: SAGE Publications
Date: 10-2018
Abstract: Direct yaw-moment control systems have been proven effective in enhancing vehicle stability and handling. The existing direct yaw-moment control designs commonly involve computation of tire side-slip angles, which is susceptible to measurement and estimation errors. The fixed control gain of the conventional sliding mode direct yaw-moment control design cannot adapt to variations and uncertainties in vehicle parameters. As a result, its robustness against parametric variations and uncertainties is limited. To improve the control performance, a novel adaptive sliding mode direct yaw-moment control approach is proposed in this article for electric vehicles with independent motors. The proposed method utilizes a varying control gain to adapt to the variations of front and rear tire side-slip angles. Comparative simulation results show that the proposed scheme outperforms the conventional method with inaccurate tire side-slip angle feedback. With the proposed direct yaw-moment control system on-board, the adverse effects of inaccuracies on tire side-slip angles are suppressed and the vehicle’s robustness against parametric variations and uncertainties is enhanced.
Convolutional neural networks for texture recognition using transfer learning
Publisher: IEEE
Date: 10-2017
Centralized Multiple-View Information Fusion for Multi-Object Tracking Using Labeled Multi-Bernoulli Filters
Publisher: IEEE
Date: 10-2018
Position sensing in brake-by-wire callipers using resolvers
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2006
Missing data compensation for safety-critical components in a drive-by-wire system
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2005
Theoretical analysis of hough transform optimal cell size: Segmentation of nearby lines
Publisher: IEEE
Date: 11-2015
Tracking of targets of interest using labeled multi-Bernoulli filter with multi-sensor control
Publisher: Elsevier BV
Date: 06-2020
Cauchy-Schwarz divergence-based distributed fusion with poisson random finite sets
Publisher: IEEE
Date: 10-2017
Visual tracking in background subtracted image sequences via multi-bernoulli filtering
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2013
Multiple instance-based video anomaly detection using deep temporal encoding–decoding
Publisher: Elsevier BV
Date: 03-2023
Visual tracking of numerous targets via multi-Bernoulli filtering of image data
Publisher: Elsevier BV
Date: 10-2012
Robust Power Allocation for Resource-Aware Multi-Target Tracking With Colocated MIMO Radars
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Multi-Bernoulli filtering with unknown clutter intensity and sensor field-of-view
Publisher: IEEE
Date: 03-2011
Temporal Multiple Rotation Averaging on a Distributed Dynamic Network
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
The Multiple Model Vo-Vo Filter
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2017
Resource Scheduling for Distributed Multi-Target Tracking in Netted Colocated MIMO Radar Systems
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Consistency of robust estimators in multi-structural visual data segmentation
Publisher: Elsevier BV
Date: 12-2007
Multi-bernoulli sensor control via minimization of expected estimation errors
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2015
Multiagent Information Fusion for Connected Driving: A Review
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Point Pattern Feature-Based Anomaly Detection for Manufacturing Defects, in the Random Finite Set Framework
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Distributed multi-sensor fusion using generalised multi-Bernoulli densities
Publisher: Institution of Engineering and Technology (IET)
Date: 03-2017
Clamp-force estimation for a brake-by-wire system: A sensor-fusion approach
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2008
A multi-Bernoulli approach to simultaneous segmentation of multiple motions
Publisher: IEEE
Date: 11-2012
A novel high breakdown M-estimator for visual data segmentation
Publisher: IEEE
Date: 2007
Robust multi-bernoulli sensor selection for multi-target tracking in sensor networks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2013
Multiple target tracking in video data using labeled random finite set
Publisher: IEEE
Date: 12-2014
Visual Mitosis Detection and Cell Tracking Using Labeled Multi-Bernoulli Filter
Publisher: IEEE
Date: 07-2018
Vehicle Integrated Chassis Control via Multi-Input Multi-Output Sliding Mode Control
Publisher: IEEE
Date: 10-2018
Calibration of resolver sensors in electromechanical braking systems: A modified recursive weighted least-squares approach
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2007
Optimal power management of final load and electrolyser in a solar hydrogen power generation system
Publisher: Trans Tech Publications, Ltd.
Date: 02-2014
DOI: 10.4028/WWW.SCIENTIFIC.NET/AMM.511-512.661
Abstract: This paper describes a control unit for a solar-hydrogen power generation system that is capable of supplying an electrical load simultaneously with erting excess power to an electrolyser to produce hydrogen gas for storage as backup energy. The functional requirements of such a control unit are defined. The transient response time for the PEM electrolyser is studied and analyzed through experimental testing. A design of load splitting device that also performs maximum power point tracking is proposed and its performance measured experimentally. Initial results suggest that the device can accomplish both the load splitting and maximum power point tracking functions satisfactorily.
Finite sample bias of robust estimators in segmentation of closely spaced structures: A comparative study
Publisher: Springer Science and Business Media LLC
Date: 12-02-2010
Fast estimation of epipolar geometry using high breakdown M-estimators
Publisher: IEEE
Date: 12-2007
Real-time RGB-D registration and mapping in texture-less environments using ranked order statistics
Publisher: IEEE
Date: 09-2014
Constrained Sensor Control for Labeled Multi-Bernoulli Filter Using Cauchy-Schwarz Divergence
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2017
Multi-Bernoulli sample consensus for simultaneous robust fitting of multiple structures in machine vision
Publisher: Springer Science and Business Media LLC
Date: 22-03-2015
Design of exotic materials machining system
Publisher: Trans Tech Publications, Ltd.
Date: 2013
DOI: 10.4028/WWW.SCIENTIFIC.NET/AMR.633.36
Abstract: New exotic materials such as titanium alloys and carbon fiber reinforced plastics require strong hard cutters made of cubic boron nitride or polycrystalline diamond. However, the traditional mechanical diamond grinding process is slow and causes damage to the workpiece. This chapter examines the design requirements of an electrical discharge machining system that can be used to machine polycrystalline diamond tipped carbide drills. A preliminary theoretical model is described but the system complexity requires a gain scheduling approach to the control system design.
Information theoretic approach to robust multi-Bernoulli sensor control
Publisher: IEEE
Date: 06-2014
Distributed fusion with multi-Bernoulli filter based on generalized covariance intersection
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2017
Range segmentation of large building exteriors: A hierarchical robust approach
Publisher: Elsevier BV
Date: 04-2010
Estimation of clamp force in brake-by-wire systems: A step-by-step identification approach
Publisher: SAE International
Date: 03-04-2006
DOI: 10.4271/2006-01-1154
Centralized multiple-view sensor fusion using labeled multi-Bernoulli filters
Publisher: Elsevier BV
Date: 09-2018
Analytical analysis of motion separability
Publisher: Hindawi Limited
Date: 2013
DOI: 10.1155/2013/878417
Abstract: Motion segmentation is an important task in computer vision and several practical approaches have already been developed. A common approach to motion segmentation is to use the optical flow and formulate the segmentation problem using a linear approximation of the brightness constancy constraints. Although there are numerous solutions to solve this problem and their accuracies and reliabilities have been studied, the exact definition of the segmentation problem, its theoretical feasibility and the conditions for successful motion segmentation are yet to be derived. This paper presents a simplified theoretical framework for the prediction of feasibility, of segmentation of a two-dimensional linear equation system. A statistical definition of a separable motion (structure) is presented and a relatively straightforward criterion for predicting the separability of two different motions in this framework is derived. The applicability of the proposed criterion for prediction of the existence of multiple motions in practice is examined using both synthetic and real image sequences. The prescribed separability criterion is useful in designing computer vision applications as it is solely based on the amount of relative motion and the scale of measurement noise.
Sensor Control for Selective Object Tracking Using Labeled Multi-Bernoulli Filter
Publisher: IEEE
Date: 07-2018
Parametric segmentation of nonlinear structures in visual data: An accelerated sampling approach
Publisher: Springer New York
Date: 29-07-2014
Multi-Bernoulli sensor-selection for multi-target tracking with unknown clutter and detection profiles
Publisher: Elsevier BV
Date: 02-2016
Robust multi-bernoulli filtering
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2013
Semantic Guided Long Range Stereo Depth Estimation for Safer Autonomous Vehicle Applications
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2022
Information Fusion for Industrial Mobile Platform Safety via Track-Before-Detect Labeled Multi-Bernoulli Filter
Publisher: MDPI AG
Date: 29-04-2019
DOI: 10.3390/S19092016
Abstract: This paper presents a novel Track-Before-Detect (TBD) Labeled Multi-Bernoulli (LMB) filter tailored for industrial mobile platform safety applications. At the core of the developed solution is two techniques for fusion of color and edge information in visual tracking. We derive an application specific separable likelihood function that captures the geometric shape of the human targets wearing safety vests. We use a novel geometric shape likelihood along with a color likelihood to devise two Bayesian updates steps which fuse shape and color related information. One approach is sequential and the other is based on weighted Kullback–Leibler average (KLA). Experimental results show that the KLA based fusion variant of the proposed algorithm outperforms both the sequential update based variant and a state-of-art method in terms of the performance metrics commonly used in computer vision literature.
Multi-Frame Track-Before-Detect Algorithm for Maneuvering Target Tracking
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2020
3D SLAM in texture-less environments using rank order statistics
Publisher: Cambridge University Press (CUP)
Date: 21-10-2017
DOI: 10.1017/S0263574715000831
Abstract: We present a real time 3D SLAM system for texture-less scenes using only depth information provided by a low cost RGB-D sensor. The proposed method is based on a novel informative s ling scheme that extracts points carrying the most useful 3D information for registration. The aim of the proposed s ling technique is to informatively s le a point cloud into a subset of points based on their 3D information. The flatness of a point is measured by applying a rank order statistics based robust segmentation method to surface normals in its local vicinity. The extracted keypoints from sequential frames are then matched and a rank order statistics based robust estimator is employed to refine the matches and estimate a rigid-body transformation between the frames. Experimental evaluations show that the proposed keypoint extraction method is highly repeatable and outperforms the state of the art methods in terms of accuracy and repeatability. We show that the performance of the registration algorithm is also comparable to other well-known methods in texture-less environments.
Estimation of components reliability in petrochemical plants using a neural-Weibull lifetime model
Publisher: Informa UK Limited
Date: 24-03-2009
Electronic differential for high-performance electric vehicles with independent driving motors
Publisher: Inderscience Publishers
Date: 2014
Centralized Cooperative Sensor Fusion for Dynamic Sensor Network With Limited Field-of-View via Labeled Multi-Bernoulli Filter
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Nonlinearity in an electromechanical braking system: Development of a smart caliper
Publisher: Springer New York
Date: 12-2012
A Survey of CNN-Based Techniques for Scene Flow Estimation
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Conditions for segmentation of motion with affine fundamental matrix
Publisher: Springer Berlin Heidelberg
Date: 2009
Visual tracking of multiple targets by multi-Bernoulli filtering of background subtracted image data
Publisher: Springer Berlin Heidelberg
Date: 2011
Interaction-Aware Labeled Multi-Bernoulli Filter
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Interval Type 2 Fuzzy Logic Control for Energy Management of Hybrid Electric Autonomous Vehicles
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2021
Real-time clamp force measurement in electromechanical brake calipers
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2008
Labeled multi-Bernoulli tracking for industrial mobile platform safety
Publisher: IEEE
Date: 02-2017
Analysis of planar-motion segmentation using affine fundamental matrix
Publisher: Institution of Engineering and Technology (IET)
Date: 12-2014
Multiobject tracking for generic observation model using labeled random finite sets
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-01-2018
Electronic differential design for vehicle side-slip control
Publisher: IEEE
Date: 11-2012
Bayesian integration of audio and visual information for multi-target tracking using a CB-member filter
Publisher: IEEE
Date: 05-2011
Stress visualization in geometrically complex structures using Thermoelastic Stress Analysis and Augmented Reality
Publisher: ACM
Date: 09-10-2023
Limits of motion-background segmentation using fundamental matrix estimation
Publisher: IEEE
Date: 2008
Electric vehicle side-slip control via electronic differential
Publisher: Inderscience Publishers
Date: 2015
Recent Advances in Stochastic Sensor Control for Multi-Object Tracking
Publisher: MDPI AG
Date: 09-2019
DOI: 10.3390/S19173790
Abstract: In many multi-object tracking applications, the sensor(s) may have controllable states. Ex les include movable sensors in multi-target tracking applications in defence, and unmanned air vehicles (UAVs) as sensors in multi-object systems used in civil applications such as inspection and fault detection. Uncertainties in the number of objects (due to random appearances and disappearances) as well as false alarms and detection uncertainties collectively make the above problem a highly challenging stochastic sensor control problem. Numerous solutions have been proposed to tackle the problem of precise control of sensor(s) for multi-object detection and tracking, and, in this work, recent contributions towards the advancement in the domain are comprehensively reviewed. After an introduction, we provide an overview of the sensor control problem and present the key components of sensor control solutions in general. Then, we present a categorization of the existing methods and review those methods under each category. The categorization includes a new generation of solutions called selective sensor control that have been recently developed for applications where particular objects of interest need to be accurately detected and tracked by controllable sensors.
Efficient antilock braking by direct maximization of tire-road frictions
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2011
Deep Multi-instance Volumetric Image Classification with Extreme Value Distributions
Publisher: Springer International Publishing
Date: 2019
Related Organisations
Related Funding Activities
Visual Intelligence For Safe Vehicle Operation In Industrial Environment
Start Date: 2016
End Date: 2018
Funder: Australian Research Council
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End Date: 2018
Funder: Defence Science and Technology Organisation
View Funded ActivityData Fusion Techniques For Electro-Mechanical Braking Systems
Start Date: 2005
End Date: 2008
Funder: Australian Research Council
View Funded ActivityCrowd Tracking And Visual Analytics For Rapidly Deployable Imaging Devices
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End Date: 2018
Funder: Australian Research Council
View Funded ActivityMulti-object Estimation For Live-cell Microscopy
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End Date: 2018
Funder: Australian Research Council
View Funded ActivityIntelligent Collision Avoidance System For Mobile Industrial Platforms
Start Date: 2013
End Date: 2016
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View Funded ActivityA Stochastic Geometric Framework For Bayesian Sensor Array Processing
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End Date: 2015
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View Funded ActivityDiscovery Projects - Grant ID: DP130104404
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End Date: 12-2016
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View Funded ActivityDiscovery Projects - Grant ID: DP160104662
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End Date: 12-2020
Amount: $419,552.00
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View Funded ActivityLinkage Projects - Grant ID: LP190100165
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End Date: 12-2023
Amount: $281,205.00
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View Funded ActivityLinkage Projects - Grant ID: LP160100662
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End Date: 12-2020
Amount: $285,000.00
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View Funded ActivityLinkage Projects - Grant ID: LP130100521
Start Date: 07-2013
End Date: 12-2016
Amount: $252,000.00
Funder: Australian Research Council
View Funded ActivityLinkage Projects - Grant ID: LP160101081
Start Date: 12-2016
End Date: 12-2020
Amount: $234,098.00
Funder: Australian Research Council
View Funded Activity