Geological Literature Search (GEOLIS) (Geological Survey of Japan / AIST)

Architecture of the convolutional neural network suitable for the automatic identification of trace fossils to evaluate bioturbation intensity (HCG22-P04)(poster session)(abs.)

Authors=Kazuki Kikuchi, Hajime Naruse

Journal/Book_names=Abstracts, Japan Geoscience Union Meeting (online)

volume=2023

pages=HCG22-P04

Publish_year=2023

Publisher=Japan Geoscience Union

Language_of_Text=EN

ID=300036099

@id=https://gbank.gsj.jp/ld/resource/geolis/300036099