On December, 11 of 2020, an contribution authored by Maria João Sousa, Alexandra Moutinho and Miguel Almeida [1], was presented in the proposal track of the peer-reviewed international workshop, Tackling Climate Change with Machine Learning at the conference Neural Information Processing Systems (NeurIPS).
The proposal addresses the development of expert-in-the-loop systems that combine the benefits of semi-automated data annotation with relevant domain knowledge expertise, towards the generation of large-scale image databases for relevant wildfire tasks to empower the application of machine learning techniques in wildfire intelligence in real scenarios.
The proposal manuscript is openly available online at the workshop webpage (https://www.climatechange.ai/papers/neurips2020/90) alongside the presentation slides, which are also made available on this page.
Reference:
[1] M.J. Sousa, A. Moutinho and M. Almeida, “Expert-in-the-loop Systems Towards Safety-critical Machine Learning Technology in Wildfire Intelligence,” NeurIPS 2020 workshop: Tackling Climate Change with Machine Learning.
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