This study achieved automatic detection of rice blast fungus spores in the mixture with other fungal spores and rice pollens commonly encountered under field ...
Article "Automatic Detection of Stored Grain Fungal Spores Based on Deep Learning" Detailed information of the J-GLOBAL is an information service managed by ...
Feb 19, 2024 · This study achieved automatic detection of rice blast fungus spores in the mixture with other fungal spores and rice pollens commonly ...
A fungal spore detector, FSNet, based on deep learning was proposed to automatically recognize and count fungal spores ... of stored-grain insects using deep ...
Apr 25, 2024 · Hongfei Bao, Junhao Luo, Jiangtao Li, Haiyang Zhang, Huiling Zhou: Automatic Detection of Stored Grain Fungal Spores Based on Deep Learning.
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A fungal spore detector, FSNet, based on deep learning was proposed to automatically recognize and count fungal spores in microscopic images. A framework based ...
The Gray Mold Spore Detection of Cucumber Based on Microscopic ...
www.ncbi.nlm.nih.gov › PMC10013786
Jan 10, 2023 · The Gray Mold Spore Detection of Cucumber Based ... An automatic detector for fungal spores in microscopic images based on deep learning.
Sep 11, 2018 · The quantitative monitoring of airborne urediniospores of Puccinia striiformis f. sp. tritici (Pst) using spore trap devices in wheat fields ...
Pyricularia Oryzae is a type of fungal spores which can lead to the most damaging rice blast disease. We have developed a quick and robust tool for counting ...
Fungal spores were considered to be a key indicator for grain storage security, because they reflect the early mildew status of stored grain, and can also be ...