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"UDE DIATOMS in the Wild 2024":一个新的淡水藻图像数据集,用于训练深度学习模型

Aishwarya Venkataramanan1,2,3, Michael Kloster4, Andrea Burfeid-Castellanos4

  • 1Université de Lorraine, CNRS, LIEC, F-57000 Metz, France.

GigaScience
|November 28, 2024
PubMed
概括

本研究介绍了用于深度学习的最大的藻图像数据集,有助于生态研究和环境状况评估. 该数据集解决了识别微藻的挑战,促进了人工智能驱动的分类学识别.

关键词:
水生生态学 水生生态学深度学习是一种深度学习.藻类是一种藻类.数字成像数字成像光显微镜光学显微镜在分销之外的检测检测.半监督学习 半监督学习幻灯片扫描扫描 幻灯片扫描

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