Unverified paper record
Deep Learning for Field-Based Cereal Phenomics
DalSpace (Dalhousie University) · 15 May 2026
Abstract
PhD thesis investigating deep learning methods for non-destructive, high-throughput phenotyping in cereal crops, covering NIRS, hyperspectral imaging, UAV-based plot segmentation, image-based disease assessment, and cross-platform deployment of phenomics pipelines.
Plant phenotyping relevance
穀類の非破壊・高スループット表現型解析を中心に、深層学習、NIRS、ハイパースペクトル画像、UAV画像分割、病害評価、フェノミクス基盤展開を扱う方法研究である。
abstractPhD thesis investigating deep learning methods for non-destructive, high-throughput phenotyping in cereal crops, covering NIRS, hyperspectral imaging, UAV-based plot segmentation, image-based disease assessment, and cross-platform deployment of phenomics pipelines.
Code and data availability
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