DOI | Trouver le DOI : https://doi.org/10.1007/978-3-031-37731-0_35 |
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Auteur | Rechercher : Power, JoshuaIdentifiant ORCID : https://orcid.org/0000-0002-2536-8034; Rechercher : Jacoby, DerekIdentifiant ORCID : https://orcid.org/0000-0002-1552-7484; Rechercher : Drouin, Marc-Antoine1Identifiant ORCID : https://orcid.org/0000-0001-8344-0842; Rechercher : Durand, Guillaume1; Rechercher : Coady, Yvonne; Rechercher : Meng, Julian |
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Affiliation | - Conseil national de recherches du Canada. Technologies numériques
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Format | Texte, Article |
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Conférence | Pattern Recognition, Computer Vision, and Image Processing, ICPR 2022 International Workshops and Challenges, August 21–25, 2022, Montreal, QC, Canada |
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Sujet | aerial survey; image quality metric; glare; neural networks; marine megafauna; machine learning; data-driven mission planning |
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Résumé | Critically endangered species in Canadian North Atlantic waters are systematically surveyed to estimate species populations which influence governing policies. Due to its impact on policy, population accuracy is important. This paper lays the foundation towards a data-driven glare modelling system, which will allow surveyors to preemptively minimize glare. Surveyors use a detection function to estimate megafauna populations which are not explicitly seen. A goal of the research is to maximize useful imagery collected, to that end we will use our glare model to predict glare and optimize for glare-free data collection. To build this model, we leverage a small labelled dataset to perform semi-supervised learning. The large dataset is labelled with a Cascading Random Forest Model using a naïve pseudo-labelling approach. A reflectance model is used, which pinpoints features of interest, to populate our datasets which allows for context-aware machine learning models. The pseudo-labelled dataset is used on two models: a Multilayer Perceptron and a Recurrent Neural Network. With this paper, we lay the foundation for data-driven mission planning; a glare modelling system which allows surveyors to preemptively minimize glare and reduces survey reliance on the detection function as an estimator of whale populations during periods of poor subsurface visibility. |
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Date de publication | 2023-08-10 |
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Maison d’édition | Springer Nature |
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Dans | |
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Série | |
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Langue | anglais |
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Publications évaluées par des pairs | Oui |
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Exporter la notice | Exporter en format RIS |
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Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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Identificateur de l’enregistrement | 256862bd-d96d-45c6-958f-e488ec1c9cfe |
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Enregistrement créé | 2023-11-03 |
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Enregistrement modifié | 2023-11-03 |
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