Solve it or Ignore it? The Challenge of Alignment Distortion and Creating Next Generation Automatic Facial Expression Detection. The last two decades have seen an escalating interest in automating the coding of facial expressions. Despite this keen interest, the promise of computer vision systems to accurately code facial expressions in natural circumstances remains elusive. Our interdisciplinary team will research a new paradigm to account for facial alignment distortion directly rather than ai ....Solve it or Ignore it? The Challenge of Alignment Distortion and Creating Next Generation Automatic Facial Expression Detection. The last two decades have seen an escalating interest in automating the coding of facial expressions. Despite this keen interest, the promise of computer vision systems to accurately code facial expressions in natural circumstances remains elusive. Our interdisciplinary team will research a new paradigm to account for facial alignment distortion directly rather than aiming to achieve invariance to it. The project will also research new data agnostic feature compaction capabilities to enable scalable learning on the world’s largest and challenging expression dataset available to us through international collaboration. Tackling these two major open problems will make accurate coding of facial expressions in natural environments achievable.Read moreRead less
Omniscient face recognition for uncooperative subjects. The outcomes of this project will enable effective video surveillance technology to be developed for use by law enforcement and national security agencies. It will lead to reliable identification of humans at a distance by automatically detecting and recognising faces, for use in counter-terrorism surveillance and commercial robot-human interfaces.
High resolution single particle analysis of biological macromolecules. One of the great challenges of cell biology is to increase the rate of atomic resolution structure determination, particularly of membrane proteins and macromolecular assemblies. The current rate-limiting step is high quality crystal production. Our goal is to prove that protein structures can be determined to atomic resolution by single-particle analysis. 3D structures will be produced by computationally aligning high-resolu ....High resolution single particle analysis of biological macromolecules. One of the great challenges of cell biology is to increase the rate of atomic resolution structure determination, particularly of membrane proteins and macromolecular assemblies. The current rate-limiting step is high quality crystal production. Our goal is to prove that protein structures can be determined to atomic resolution by single-particle analysis. 3D structures will be produced by computationally aligning high-resolution electron microscope images of individual, randomly oriented molecules. The importance of this project is highlighted by the fact over 120,000 protein sequences are already databased, a number set to increase rapidly as new genome sequencing projects are completed.
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Improved detection and characterisation of breast cancer using magnetic resonance imaging, and novel image analysis and pattern recognition techniques. Breast cancer is a leading cause of death in Australian women. With no clear cause, one mainstay of management has been early detection. Newer medical imaging technologies such as magnetic resonance imaging require complex analysis to achieve their full benefit. Should the computationally demanding analyses of these images provide more sensitive ....Improved detection and characterisation of breast cancer using magnetic resonance imaging, and novel image analysis and pattern recognition techniques. Breast cancer is a leading cause of death in Australian women. With no clear cause, one mainstay of management has been early detection. Newer medical imaging technologies such as magnetic resonance imaging require complex analysis to achieve their full benefit. Should the computationally demanding analyses of these images provide more sensitive and specific detection of early cancers, the potential reductions in morbidity and mortality from breast cancer will be of immense value. Successful implementation of the proposed project will further enhance Australia's position as a world leader in biomedical research and application of computational technologies to health problems.Read moreRead less
Dielectric contrast imaging for 7 Tesla magnetic resonance applications. This project aims to develop novel radio-frequency (RF) technology, ensuring that the benefits of high-field magnetic resonance imaging (MRI) are available for a broader range of applications. This project will develop a new contrast mechanism directly related to the RF properties of individual tissue types, circumventing a limitation of intensity based imaging. This technology will enhance Australia’s global impact the dev ....Dielectric contrast imaging for 7 Tesla magnetic resonance applications. This project aims to develop novel radio-frequency (RF) technology, ensuring that the benefits of high-field magnetic resonance imaging (MRI) are available for a broader range of applications. This project will develop a new contrast mechanism directly related to the RF properties of individual tissue types, circumventing a limitation of intensity based imaging. This technology will enhance Australia’s global impact the development of imaging technology for healthcare, biomedical research and advanced diagnostics.Read moreRead less
Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features t ....Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features to analyse in each modality and the hidden relationships between them. The use of deep belief networks has produced promising results in several fields, such as speech recognition, and so this project believes that our approach has the potential to improve both the sensitivity and specificity of breast cancer detection.Read moreRead less
Advanced Magnetic Resonance Imaging at 7 Tesla: Resolving the fundamental radiofrequency field-tissue interaction problem at ultra-high field. Ultra-high-field Magnetic Resonance Imaging (MRI) systems offer the potential for faster, more accurate diagnostic imaging. However, current applications are limited by the fundamental challenge of strong interactions between the electromagnetic field and human tissues, which result in poor image quality and/or compromised patient safety. Using a novel, s ....Advanced Magnetic Resonance Imaging at 7 Tesla: Resolving the fundamental radiofrequency field-tissue interaction problem at ultra-high field. Ultra-high-field Magnetic Resonance Imaging (MRI) systems offer the potential for faster, more accurate diagnostic imaging. However, current applications are limited by the fundamental challenge of strong interactions between the electromagnetic field and human tissues, which result in poor image quality and/or compromised patient safety. Using a novel, subject-specific imaging approach, this research will design and develop an ultra-high-field radiofrequency technology capable of offering high-performance imaging without jeopardising patient safety. This research will lay the groundwork for the translation of ultra-high field MRI research into clinical practice, generating new capabilities for diagnostic technologies.Read moreRead less
Techniques to use stereo vision for improving person identification systems based on face recognition. The broad aim of this project is to use three-dimensional information available by processing images from stereo cameras in order to bridge the gap between constrained face recognition systems and viable systems that work well under varying illumination, changes in pose and variations in spectacles, facial hair and attire. Such a system will be useful in passenger verification at airports and a ....Techniques to use stereo vision for improving person identification systems based on face recognition. The broad aim of this project is to use three-dimensional information available by processing images from stereo cameras in order to bridge the gap between constrained face recognition systems and viable systems that work well under varying illumination, changes in pose and variations in spectacles, facial hair and attire. Such a system will be useful in passenger verification at airports and as a component of personal identification systems to counter terrorism. The key to successful face location and recognition is an effective combination of all data - range, luminance and colour - and techniques for this will be the discovered outcomes.Read moreRead less
Linking human brain structure to function with ultra-high resolution fMRI. This project will examine the structure and function of the sensory cortex of the human brain using ultra-high resolution functional magnetic resonance imaging (7 Tesla MRI). The project pushes new boundaries for resolution with ultra-high field MRI (7 Tesla) and, as such, will advance techniques for the acquisition, analysis, and computational modelling of high-resolution fMRI brain imaging, providing detail of the funct ....Linking human brain structure to function with ultra-high resolution fMRI. This project will examine the structure and function of the sensory cortex of the human brain using ultra-high resolution functional magnetic resonance imaging (7 Tesla MRI). The project pushes new boundaries for resolution with ultra-high field MRI (7 Tesla) and, as such, will advance techniques for the acquisition, analysis, and computational modelling of high-resolution fMRI brain imaging, providing detail of the functional organisation of the sensory cortex at a level never previously possible in the living human brain. This will provide new understanding of the neural-level networks that underpin attention and touch perception in the human brain.Read moreRead less
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