| _version_ | 1866902264704139264 |
|---|---|
| author | Sinnott, Richard |
| author_facet | Sinnott, Richard |
| contents | 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. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_15293511 |
| institution | Zenodo |
| language | |
| publishDate | 2024 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Supporting Deep Learning Solutions for Diverse Application Domains Sinnott, Richard Machine Learning Analytics Software Deep Learning Infrastructure Data AI 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. |
| title | Supporting Deep Learning Solutions for Diverse Application Domains |
| topic | Machine Learning Analytics Software Deep Learning Infrastructure Data AI |
| url | https://doi.org/10.5281/zenodo.15293511 |