A5067249512- Advanced Vision and Imaging
- Target Tracking and Data Fusion in Sensor Networks
- Robotics and Sensor-Based Localization
- Distributed Sensor Networks and Detection Algorithms
- Advanced Image and Video Retrieval Techniques
- Anomaly Detection Techniques and Applications
- Image and Object Detection Techniques
- Video Surveillance and Tracking Methods
- Remote Sensing and LiDAR Applications
- Electric and Hybrid Vehicle Technologies
- Vehicle Dynamics and Control Systems
- 3D Surveying and Cultural Heritage
- Medical Image Segmentation Techniques
- Fault Detection and Control Systems
- Image Processing Techniques and Applications
- Advanced Image Processing Techniques
- Industrial Vision Systems and Defect Detection
- Optical measurement and interference techniques
- Infrared Target Detection Methodologies
- Gaussian Processes and Bayesian Inference
- Additive Manufacturing Materials and Processes
- Advanced Statistical Methods and Models
- 3D Shape Modeling and Analysis
- Sensor Technology and Measurement Systems
- Sparse and Compressive Sensing Techniques
RMIT University
2015-2024
MIT University
2019-2024
RMIT Europe
2024
The Royal Melbourne Hospital
2018-2023
ORCID
2021
Institute of Engineering
2017
Swinburne University of Technology
2003-2011
Monash University
1995-2002
Australian Regenerative Medicine Institute
1997
Retinal swelling due to the accumulation of fluid is associated with most vision-threatening retinal diseases. Optical coherence tomography (OCT) current standard care in assessing presence and quantity image-guided treatment management. Deep learning methods have made their impact across medical imaging, many OCT analysis been proposed. However, it currently not clear how successful they are interpreting on OCT, which lack standardized benchmarks. To address this, we organized a challenge...
Resolver sensors are utilized as absolute position transducers to control the and speed of actuators in many industrial applications. The accuracy convergence measurements provided by resolvers electromechanical braking system (EMB) designs directly contribute performance vehicle safety. In practice, dc drifts, amplitudes, phase shift resolver signals vary with aging temperature, adaptive techniques required for calibration these parameters resolvers. Existing classical such recursive least...
Autonomous vehicles are aimed to reduce accidents and traffic congestion. Since hybrid electric offer feasible solutions energy consumption emission the environment, it is expected that autonomous will be powered through a system compared other alternatives. In this paper, vehicle studied under significant amount of uncertainty ambiguity in road environment driver behavior. A Type 1 fuzzy logic controller constructed here address uncertainties driving conditions. The design involves building...
To meet the challenges of manufacturing smart products, plants have been radically changed to become factories underpinned by industry 4.0 technologies.The transformation is assisted employment machine learning techniques that can deal with modeling both big or limited data.This manuscript reviews these concepts and present a case study demonstrates use novel intelligent hybrid algorithms for Industry applications data.In particular, an algorithm proposed robust data nonlinear systems based...
This letter addresses the sensor selection problem for tracking multiple dynamic targets within a network. Since bandwidth and energy of network are constrained, it would not be feasible to directly use entire information nodes detection hence need selection. Our solution is formulated using multi-Bernoulli random finite set framework. The proposed method selects minimum subset sensors which most likely provide reliable measurements. overall scheme robust that works in challenging scenarios...
Identifying the underlying model in a set of data contaminated by noise and outliers is fundamental task computer vision. The cost function associated with such tasks often highly complex, hence most cases only an approximate solution obtained evaluating on discrete locations parameter (hypothesis) space. To be successful at least one hypothesis has to vicinity solution. Due hypotheses generated minimal subsets can far from model, even when samples are said structure. In this paper we...
The design of electric vehicles (EVs) is increasingly based upon using the in-wheel technology. In this design, use a separate machine at each corner vehicle provides unique opportunities for innovative control strategies. paper, sensorless antilock braking system (ABS) proposed that eliminates need installation conventional ABS sensors and saves costs associated with maintenance those EVs. exploits information carried by back electromotive force (EMF) machines to obtain accurate wheel speed...
This paper presents a sensor-control method for choosing the best next state of sensors that provide accurate estimation results in multitarget tracking application. The proposed solution is formulated multi-Bernoulli filter and works via minimization new estimation-error-based cost function. Simulation demonstrate can outperform state-of-the-art methods terms computation time robustness to clutter while delivering similar accuracy.
Brushless motors are increasingly used in different designs of in-wheel electric vehicles (EVs). In this paper, a sensorless antilock braking system (ABS) for brushless-motor EVs is proposed. The proposed solution omits the need installation separate conventional ABS sensors at each corner vehicle. This paper also shows, both theoretically and experimentally, that general form sensor output voltage identical to brushless dc (BLDC)-motor back electromotive force. can reduce costs...
This paper proposes a novel method in order to obtain voxel-level segmentation for three fluid lesion types (IR-F/SRF/PED) OCT images provided by the ReTOUCH challenge [1]. The is based on deep neural network consisting of encoding and de-coding blocks connected with skip-connections which was trained using combined cost function comprising cross-entropy, dice adversarial loss terms. results held-out validation set shows that architecture functions used has resulted improved retinal...
State-of-the-art stereo matching networks trained only on synthetic data often fail to generalize more challenging real domains. In this paper, we attempt unfold an important factor that hinders the from generalizing across domains: through lens of shortcut learning. We demonstrate learning feature representations in is heavily influenced by artefacts (shortcut attributes). To mitigate issue, propose Information-Theoretic Shortcut Avoidance (ITSA) approach automatically restrict...
In this paper, we propose an efficient approach for industrial defect detection that is modeled based on anomaly using point pattern data. Most recent works use \textit{global features} feature extraction to summarize image content. However, global features are not robust against lighting and viewpoint changes do describe the image's geometrical information be fully utilized in manufacturing industry. To best of our knowledge, first transfer learning local/point overcome these limitations...