Supporting Deep Learning Solutions for Diverse Application Domains

The Melbourne eResearch Group (www.eresearch.unimelb.edu.au) are involved in a multitude of projects, many of which are focused on big data and data analytics. Many researcher challenges have much to benefit from artificial intelligence and especially from the application of deep learning technologies. This talk will cover diverse areas where practical solutions have been designed and delivered to customers by the Melbourne eResearch Group including: Identifying specific vehicles (trucks) on the road network of Melbourne and estimating their associated speed through roadside cameras; Identifying platypus from remote cameras for ecology researchers; Identifying unique feral cats for ecology researchers; Evaluating the spread of bushfires through satellite imagery and especially in dealing with noisy data, e.g. where there are Clouds and smoke; Automatically recognising and classifying the actions and events that take place in AFL games. The talk will cover a brief background to deep learning and focus on the results that are now possible, highlighting the above examples with demonstrations of the results.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-30
DOI
https://doi.org/10.5281/zenodo.15293510
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
0.00
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article

Supporting Deep Learning Solutions for Diverse Application Domains

Zenodo (CERN European Organization for Nuclear Research)
Research Data Management Practices
article

Supporting Deep Learning Solutions for Diverse Application Domains

article en

Abstract

The Melbourne eResearch Group (www.eresearch.unimelb.edu.au) are involved in a multitude of projects, many of which are focused on big data and data analytics. Many researcher challenges have much to benefit from artificial intelligence and especially from the application of deep learning technologies. This talk will cover diverse areas where practical solutions have been designed and delivered to customers by the Melbourne eResearch Group including: Identifying specific vehicles (trucks) on the road network of Melbourne and estimating their associated speed through roadside cameras; Identifying platypus from remote cameras for ecology researchers; Identifying unique feral cats for ecology researchers; Evaluating the spread of bushfires through satellite imagery and especially in dealing with noisy data, e.g. where there are Clouds and smoke; Automatically recognising and classifying the actions and events that take place in AFL games. The talk will cover a brief background to deep learning and focus on the results that are now possible, highlighting the above examples with demonstrations of the results.

Zenodo (CERN European Organization for Nuclear Research)
The University of Melbourne (AU)
Openalex Percentile: Top 38%
Research Data Management Practices
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Supporting Deep Learning Solutions for Diverse Application Domains · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS