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Neuromorphic Computational Imaging
Supervisors
Dr Nimrod Kruger & Prof Paul Hurley
Description
Considering common imaging methods, optical elements are used to project a scene onto a sensor, which then records this projection as an image we are familiar with. Alternatively, computational imaging techniques take the approach of processing data collected from unique non-imaging optical systems, often by utilising the Fourier optics approach, to extract new information for various tasks. Like with computational imaging, neuromorphic (event-based) sensing has also refreshed the way scientists and engineers process the data recorded by the sensor. This refreshed view begs us to explore the combination of event-based sensing with computational imaging paradigms.
This project will search the space of Fourier optics and computational imaging with event-based sensing to uncover novel real-time sensing modalities in microscopy, inspection, and computer vision.
Eligibility Criteria
Background in Mathematics, Physics, or Electrical Engineering.
About ICNS
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Projects
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- Task-Driven Model Evaluation in Large-Scale Spiking Neural Networks
- A Neuromorphic Ferroelectric field-effect Ultra-Scaled Chip for Spiking Neural Networks
- Event Based Wavefront Sensing Modalities
- Physics-Based Encoding for Spiking Neural Networks
- Neuromorphic Computational Imaging
- Defining Performance Metrics for Closed Loop Event Based Imaging Systems
- A Neuromorphic Framework for Event-Based DNNs using Minifloats
- A RISC-V instruction set architecture (ISA) extensions for neuromorphic computing using minifloats
- Astrometry with Event-based Vision Sensors
- Automatic Evaluation of Bushfire Risk via Acoustic Scene Analysis
- Bio-inspired Sensors for Space Situational Awareness
- Building a Neuromorphic Auditory Pathway for Sensing the Surrounding Environment
- Cold Start Astrometry for High-Precision Airspace and Space Objects Tracking with Neuromorphic Cameras
- Control Systems Inspired by Insect Central Pattern Generators that can Adapt to Dynamic Environments.
- Design of Neuromorphic Spiking Neural Networks for Real-Time Processing
- Enhanced Maritime Situational Awareness with Neuromorphic Cameras
- Environmental Situational Awareness using Neuromorphic Vision Sensors and IMU-based SLAM
- Fault Tolerant Distributed Swarm Intelligence using Neuromorphic Computing and Local Learning Principles
- Honey Bee Waggle Dance Detection via Neuromorphic Engineering
- Integrated Circuit Design for Event-based Vision Sensors
- Low-Power Acoustic Ecological Monitoring in Remote Areas using Machine Learning and Neuromorphic Engineering
- Neuromorphic Computing in Extreme Environments
- Neuromorphic Cyber Security at the Edge
- Neuromorphic Engineering for Acoustic Aerial Drone Detection in Visually Obscured Environments
- Machine Learning-Based Tool for Therapists to Monitor Speech Progress in Late Talkers
- Machine Learning for Automated Child Reading Assessment and Intervention
- Underwater Acoustic Drone Detection via Neuromorphic Models of Marine Mammal Audition
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