Lars Nieradzik, Jördis Sieburg-Rockel, Stephanie Helmling, Janis Keuper, Thomas Weibel, Andrea Olbrich, Henrike Stephani
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引用次数: 0
Abstract
We have developed a methodology for the systematic generation of a large image dataset of macerated wood references, which we used to generate image data for nine hardwood genera. This is the basis for a substantial approach to automate, for the first time, the identification of hardwood species in microscopic images of fibrous materials by deep learning. Our methodology includes a flexible pipeline for easy annotation of vessel elements. We compare the performance of different neural network architectures and hyperparameters. Our proposed method performs similarly well to human experts. In the future, this will improve controls on global wood fiber product flows to protect forests.
期刊介绍:
Microscopy and Microanalysis publishes original research papers in the fields of microscopy, imaging, and compositional analysis. This distinguished international forum is intended for microscopists in both biology and materials science. The journal provides significant articles that describe new and existing techniques and instrumentation, as well as the applications of these to the imaging and analysis of microstructure. Microscopy and Microanalysis also includes review articles, letters to the editor, and book reviews.