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Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2021.3140118
Abstract: Fabric defect detection is a challenging task in the fabric industry because of the complex shapes and large variety of fabric defects. Many methods have been proposed to solve this problem, but their detection speed…
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Keywords:
fabric defect;
structure;
defect detection;
improved yolov4 ... See more keywords
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Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/6106853
Abstract: UAV (unmanned aerial vehicle) captured images have small pedestrian targets and loss of key information after multiple down sampling, which are difficult to overcome by existing methods. We propose an improved YOLOv4 model for pedestrian…
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Keywords:
pedestrian detection;
detection counting;
counting uav;
feature ... See more keywords
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2
Published in 2023 at "Frontiers in Neurorobotics"
DOI: 10.3389/fnbot.2023.1119896
Abstract: Introduction The surface images of steel rails are extremely difficult to detect and recognize due to the presence of interference such as light changes and texture background clutter during the acquisition process. Methods To improve…
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Keywords:
rail defects;
rail;
surface;
defects detection ... See more keywords
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Published in 2022 at "Frontiers in Plant Science"
DOI: 10.3389/fpls.2022.1030021
Abstract: Accurate recognition method of pitaya in natural environment provides technical support for automatic picking. Aiming at the intricate spatial position relationship between pitaya fruits and branches, a pitaya recognition method based on improved YOLOv4 was…
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Keywords:
recognition;
coordinate attention;
yolov4 recognition;
improved yolov4 ... See more keywords
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Published in 2022 at "Frontiers in Plant Science"
DOI: 10.3389/fpls.2022.814681
Abstract: Tomato plants are infected by diseases and insect pests in the growth process, which will lead to a reduction in tomato production and economic benefits for growers. At present, tomato pests are detected mainly through…
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Keywords:
algorithm based;
tomato pest;
based improved;
improved yolov4 ... See more keywords
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2
Published in 2023 at "Frontiers in Plant Science"
DOI: 10.3389/fpls.2023.1150958
Abstract: Automatic and accurate detection of fruit in greenhouse is challenging due to complicated environment conditions. Leaves or branches occlusion, illumination variation, overlap and cluster between fruits make the fruit detection accuracy to decrease. To address…
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Keywords:
tomato detection;
yolov4 tiny;
improved yolov4;
detection ... See more keywords