COMP 6002 Neuromorphic Sensing
Credit Points 10
Legacy Code 800233
Coordinator Gregory Cohen Opens in new window
Description Neuromorphic sensors offer a new way to electronically sense and process data that have a unique structure based on principles found in biology. Understanding how they operate is integral to their effective use in practical situations, to the development of algorithms, process their data, and to the optimisation of their electronic designs. This subject focuses primarily on neuromorphic vision sensors, which are rapidly being adopted by multiple industries, including exciting applications in automotive and space. Students will develop an in-depth understanding of neuromorphic sensors and the skills to operate a neuromorphic sensor for acquiring data and solving real-world problems. This practical experience is in high demand from both research labs and the industry.
School Graduate Research School
Discipline Algorithms
Student Contribution Band HECS Band 2 10cp
Check your HECS Band contribution amount via the Fees page.
Level Postgraduate Coursework Level 6 subject
Restrictions Students must be enrolled in 8124 Master of Applied Neuromorphic Engineering
Assumed Knowledge
Basic knowledge of:
- the physical nature of light
- analogue and digital electrical circuits (filtering, transistor logic)
- computer architectures (Van Neuman architectures, microcontrollers, buses, periphericals (USB, DAC, GPIO), communication protocols)
Learning Outcomes
- Synthesize the characteristics of a scene using data captured by an event-based vision sensor
- Evaluate the differences between frame and event-based sensors
- Design an experimental setup to gather valuable data from a neuromorphic sensor with a deep appreciation of different neuromorphic sensor characteristics
- Assess the suitability of visio-tactile neuromorphic sensing for a real-world application
- Critically appraise legal, ethical and cultural issues and considerations in the context of the emerging field of Neuromorphic research
- Report data and analysis in accordance with professional standards
Subject Content
2. The different architectures of vision sensors
3. Biological sensors
- Retina: organization, key experiments, optic nerve, 6 control muscle
- Retina: organization, key experiments, optic nerve, 6 control muscle
- Tactile
- Olfactory
4. Neuromorphic vision sensors
- The event-based pixel: architecture, characteristics
- Sensors?f evolutions: ATIS, DAVIS, Celex.
5. Neuromorphic auditory sensors
- Artificial cochlea: filters, analogue vs digital implementation
- Auditory nerve: spike generation
- Brainstem: Auditory feature extraction and analysis
6. Research methods
7. Sensing technology and emerging legal, ethical and cultural considerations
8. Data collection and analysis
9. Guidelines for journal paper writing
Assessment
The following table summarises the standard assessment tasks for this subject. Please note this is a guide only. Assessment tasks are regularly updated, where there is a difference your Learning Guide takes precedence.
Type | Length | Percent | Threshold | Individual/Group Task |
---|---|---|---|---|
Viva Voce | 3000 words or equivalent | 20 | N | Group |
Report | 1000 words or equivalent | 30 | N | Individual |
Practical | 4000 words or equivalent | 50 | N | Individual |
Teaching Periods
Spring (2022)
Parramatta City - Macquarie St
Day
Subject Contact Gregory Cohen Opens in new window
View timetable Opens in new window
Spring (2023)
Parramatta City - Macquarie St
On-site
Subject Contact Gregory Cohen Opens in new window