This neural network extracted multi-scale feature maps of insects to detect them. The insects is mixed with fines, foreign materials, dockages and broken ...
This paper applied the object detection algorithm, which was based on Faster R-CNN, to detect stored-grain insects under field condition with impurities.
Sep 4, 2020 · This paper proposes an improved detection neural network architecture based on R-FCN to solve the problem of detection and classification of ...
Shen et al. [17] proposed a faster-RCNN framework based on a convolutional neural network to detect 6 stored grain pests with an accuracy rate of 88.02%.
A detection and identification method for stored-grain insects was developed by applying deep neural network. Adults of following six species of common ...
A detection and identification method for stored-grain insects was developed by applying deep neural network. Adults of following six species of common ...
A detection and identification method for stored-grain insects was developed by applying deep neural network. Adults of following six species of common ...
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An improved detection neural network architecture based on R-FCN is proposed to solve the problem of detection and classification of eight common stored ...
Mar 22, 2023 · Machine vision has constantly been evolving as a technique for insect detection in stored grains. One of the first studies published was on ...
Jun 7, 2023 · Overall, the study provides an excellent preliminary evaluation of one method for in-situ monitoring of insects in stored grain.