Artificial intelligence as a potential tool for micro-histological analysis of herbivore diets
Author:
Funder
Ministerio de Ciencia, Innovación y Universidades
Publisher
Springer Science and Business Media LLC
Subject
Management, Monitoring, Policy and Law,Nature and Landscape Conservation,Ecology, Evolution, Behavior and Systematics
Link
https://link.springer.com/content/pdf/10.1007/s10344-022-01640-4.pdf
Reference20 articles.
1. Aono AH, Nagai JS, Dickel GdSM, Marinho RC, de Oliveira PEAM, Papa JP, Faria FA (2021) A stomata classification and detection system in microscope images of maize cultivars. PLoS ONE 16:e0258679. https://doi.org/10.1371/journal.pone.0258679
2. Bartolome J, Franch J, Gutman M, Seligman NG (1995) Physical factors that influence fecal analysis estimates of herbivore diets. J Range Manage 48:267–270. https://doi.org/10.2307/4002432
3. Bartolome J, Franch J, Plaixats J, Seligman NG (1998) Diet selection by sheep and goats on Mediterranean heath-woodland range. J Range Manage 51:383–391. https://doi.org/10.2307/4003322
4. Bochkovskiy A, Wang CY, Liao HYM (2020) YOLOv4: optimal speed and accuracy of object detection. https://arxiv.org/abs/2004.10934https://doi.org/10.48550/arXiv.2004.10934
5. Buslaev A, Parinov A, Khvedchenya E, Iglovikov VI, Kalinin AA (2020) Albumentations: fast and flexible image augmentations. Information 11:125. https://doi.org/10.3390/info11020125
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