A Novel Automatic Neural Network Feature Extractor. This project aims to study feature extraction abilities of convolutional as well as traditional neural networks and develop a generic feature extractor which can be applied to wide variety of real-world image and non-image data. New concepts for automatic feature extraction, feature explanation, hybrid evolutionary algorithms and non-iterative ensemble learning will be introduced and evaluated. The expected outcomes are a generic feature extrac ....A Novel Automatic Neural Network Feature Extractor. This project aims to study feature extraction abilities of convolutional as well as traditional neural networks and develop a generic feature extractor which can be applied to wide variety of real-world image and non-image data. New concepts for automatic feature extraction, feature explanation, hybrid evolutionary algorithms and non-iterative ensemble learning will be introduced and evaluated. The expected outcomes are a generic feature extractor for automatically extracting features, an optimiser for finding optimal parameters and non-iterative ensemble learning technique for classification of features into classes. The impact of this project will be automatic feature extractors and classifiers for real-world applications.Read moreRead less
Smart Information Processing for Roadside Fire Risk Assessment Using Computational Intelligence and Pattern Recognition. This project proposes a novel approach for identifying roadside fire risks using pattern recognition and computational intelligence techniques. The video data is collected over every state road in Queensland annually, and has the potential to provide a range of value-added products for safer roads. This project aims to develop new techniques for identification of roadside obje ....Smart Information Processing for Roadside Fire Risk Assessment Using Computational Intelligence and Pattern Recognition. This project proposes a novel approach for identifying roadside fire risks using pattern recognition and computational intelligence techniques. The video data is collected over every state road in Queensland annually, and has the potential to provide a range of value-added products for safer roads. This project aims to develop new techniques for identification of roadside objects so that the data can be automatically analysed allowing the estimation of fire risk factors. The final outcome intends to be techniques for segmentation and classification of roadside objects and estimation of fire risk factors.Read moreRead less
Collaborative Sensing and Learning for Maritime Situational Awareness. We aim to demonstrate coordinated autonomous sensing of naval assets in dynamic maritime environments, reducing the operational load required to deliver a high quality maritime situational awareness. A realistic simulation based approach will help us develop novel artificial intelligence technology including: self-adaptive strategies for dynamic asset allocation, embedded smart sensing capabilities for naval observation syste ....Collaborative Sensing and Learning for Maritime Situational Awareness. We aim to demonstrate coordinated autonomous sensing of naval assets in dynamic maritime environments, reducing the operational load required to deliver a high quality maritime situational awareness. A realistic simulation based approach will help us develop novel artificial intelligence technology including: self-adaptive strategies for dynamic asset allocation, embedded smart sensing capabilities for naval observation systems and novel approaches to continuous collaborative learning from multi-spectral media. In addition to the emerging partnership between participants, the project will advance sovereign capability to develop maritime intelligence gathering technology for the Royal Australian Navy to underpin stability in our region. Read moreRead less
Automatic Human Age Estimation Based on Visual Information. Age verification is important for many security applications including passport control for border security, and protecting children from adult websites, venues, or products. Accurate, reliable and practical age estimation or verification technologies would be of enormous benefit for 'Safeguarding Australia'. The ability of a machine to estimate a person's age and provide an age-appropriate interface also has benefits for the young and ....Automatic Human Age Estimation Based on Visual Information. Age verification is important for many security applications including passport control for border security, and protecting children from adult websites, venues, or products. Accurate, reliable and practical age estimation or verification technologies would be of enormous benefit for 'Safeguarding Australia'. The ability of a machine to estimate a person's age and provide an age-appropriate interface also has benefits for the young and old in our society. The outcome of this project, practical technologies for automatic human age estimation based on visual information, will dramatically change the current (non-technology based) methods of age verification and create new opportunities for customised human-machine interfaces. Read moreRead less
Automatic Training Data Search and Model Evaluation by Measuring Domain Gap. We aim to investigate computer vision training data and test data, using automatically generated data sets for facial expression recognition and object re-identification. This project expects to quantify and understand the domain gap, the distribution difference between training and test data sets. Expected outcomes of this project are insights on measuring the domain gap, the ability to estimate model performance witho ....Automatic Training Data Search and Model Evaluation by Measuring Domain Gap. We aim to investigate computer vision training data and test data, using automatically generated data sets for facial expression recognition and object re-identification. This project expects to quantify and understand the domain gap, the distribution difference between training and test data sets. Expected outcomes of this project are insights on measuring the domain gap, the ability to estimate model performance without accessing expensive test labels and improvements to system generalisation. This should provide significant benefits for computer vision applications that currently require expensive labelling, and commercial and economic benefits across sectors such as transportation, security and manufacturing.Read moreRead less
Concept-based retrieval and interpretation for large data sets. Access to on-line information is growing at an exponential rate, fuelled by advances in computing and
communications technologies. Current information retrieval methods are becoming ineffective due to
their reliance on simple term-based methods, resulting in a massive number of matches, of which only
a small proportion are relevant. We address this problem by developing new matching algorithms which
understand the underlying ....Concept-based retrieval and interpretation for large data sets. Access to on-line information is growing at an exponential rate, fuelled by advances in computing and
communications technologies. Current information retrieval methods are becoming ineffective due to
their reliance on simple term-based methods, resulting in a massive number of matches, of which only
a small proportion are relevant. We address this problem by developing new matching algorithms which
understand the underlying meaning of documents in database repositories - by building semantic
structures semi-automatically - and thus provide more relevant information to queries.
This project will be of great benefit to a multitude of end-users in medicine, history, law and many other disciplines.
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Two-way Auslan: Automatic Machine Translation of Australian Sign Language. This project aims to develop an automatic two-way machine-translation system between Auslan (Australian Sign Language) and English by researching and leveraging advanced computer vision and machine learning technology. The project expects to advance research in AI technology on topics including visual recognition, language processing and deep learning. This will boost Australia's national research capacity and global com ....Two-way Auslan: Automatic Machine Translation of Australian Sign Language. This project aims to develop an automatic two-way machine-translation system between Auslan (Australian Sign Language) and English by researching and leveraging advanced computer vision and machine learning technology. The project expects to advance research in AI technology on topics including visual recognition, language processing and deep learning. This will boost Australia's national research capacity and global competitiveness. Expected outcomes of this project will help to break the communication barriers between the Deaf and hearing population. This should provide significant benefits to Deaf communities through enhanced communication and improved quality-of-life, leading to a fair, more inclusive and resilient Australian society.Read moreRead less
In search of relevant things: A novel approach for image analysis. This project aims to investigate how experts’ cognitive processes may be transferred to computers for the automatic recognition of visual features. By merging computer and brain sciences, the project will characterise the way the brains of experts understand what is seen, in order to translate such a process in a new computer vision tool. This should provide significant benefits, such as automatic detection of threats or diseases ....In search of relevant things: A novel approach for image analysis. This project aims to investigate how experts’ cognitive processes may be transferred to computers for the automatic recognition of visual features. By merging computer and brain sciences, the project will characterise the way the brains of experts understand what is seen, in order to translate such a process in a new computer vision tool. This should provide significant benefits, such as automatic detection of threats or diseases in satellite and diagnostic imaging, respectively, among other applications. For the first time, the combination of how a computer analyses an image and how an expert interprets it will be used as a common language to enable machines to process visual information in a manner that mimics the way human brains do.Read moreRead less
Automatic Machine Learning with Imperfect Data for Video Analysis . This project aims to propose new algorithms and technologies for constructing an efficient video analysis system, which will be aligned with Australia’s science and research priorities. Specifically, during this project, a novel network structure search method based on auto machine learning will be proposed, an unsupervised domain adaptation algorithm will be developed, and a generative data augmentation method will be construct ....Automatic Machine Learning with Imperfect Data for Video Analysis . This project aims to propose new algorithms and technologies for constructing an efficient video analysis system, which will be aligned with Australia’s science and research priorities. Specifically, during this project, a novel network structure search method based on auto machine learning will be proposed, an unsupervised domain adaptation algorithm will be developed, and a generative data augmentation method will be constructed. All of these will construct a stable and efficient deep neural network, which is able to process large size videos captured from real scenarios in high efficiencies. Various fields, such as health care service and cybersecurity, will benefit hugely from this project.Read moreRead less
Towards in-vehicle situation awareness using visual and audio sensors. This project aims to characterise driver awareness, activity and interactions with other vehicle occupants using visual and audio cues from internally mounted sensors. Road accidents cost Australia an estimated $30 billion per year and tragic loss of thousands of lives, yet the vast majority of severe vehicle crashes are linked to driver fatigue or distraction. The expected project outcomes include advanced artificial intelli ....Towards in-vehicle situation awareness using visual and audio sensors. This project aims to characterise driver awareness, activity and interactions with other vehicle occupants using visual and audio cues from internally mounted sensors. Road accidents cost Australia an estimated $30 billion per year and tragic loss of thousands of lives, yet the vast majority of severe vehicle crashes are linked to driver fatigue or distraction. The expected project outcomes include advanced artificial intelligence to infer and predict dangerous driver and passenger behaviour. This has the potential to significantly benefit society by advancing autonomous driving capabilities and reducing driver-induced accidents and fatalities, ensuring that every driver, passenger and pedestrian arrives home safely at the end of each day.Read moreRead less