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YOLO-P: An efficient method for pear fast detection in complex orchard picking environment
Frontiers in Plant Science, 2023 IntroductionFruit detection is one of the key functions of an automatic picking robot, but fruit detection accuracy is seriously decreased when fruits are against a disordered background and in the shade of other objects, as is commmon in a complex ...
Han Sun, Bingqing Wang, Jinlin Xue
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Fruit volatile analysis using an electronic nose. [PDF]
, 2012 Numerous and diverse physiological changes occur during fruit ripening, including the development of a specific volatile blend that characterizes fruit aroma.
Ebeler, Susan E +3 more
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YOLOMuskmelon: Quest for Fruit Detection Speed and Accuracy Using Deep Learning
IEEE Access, 2021 Fruit detection plays a vital role in harvesting robot platforms. However, complicated environment attributes such as illumination variation, occlusion, have made fruit detection a challenging task.
Olarewaju M. Lawal
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Fruit and Leaf Sensing for Continuous Detection of Nectarine Water Status [PDF]
, 2019 Continuous assessment of plant water status indicators might provide the most precise information for irrigation management and automation, as plants represent an interface between soil and atmosphere.
Lo Bianco, Riccardo +3 more
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Fruit Verity-Detecting Adulteration in fruits Using Machine Learning.
International Journal for Research in Applied Science and Engineering Technology, 2023 Abstract: Detecting fruit adulteration is a critical challenge with traditional methods often falling short due to their timeconsuming nature and high costs. Chemical tests, while common, have limitations that hinder their efficiency. Fortunately, a beacon of hope emerges in the realm of machine learning, offering a promising alternative for ...
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Management of plant health risks associated with processing of plant-based wastes: A review [PDF]
, 2009 The rise in international trade of plants and plant products has increased the risk of introduction and spread of plant pathogens and pests. In addition, new risks are arising from the implementation of more environmentally friendly methods of ...
Budge, G. E. +4 more
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Sweet Pepper Detection Using Fast Point Features Histogram and Unsupervised Learning [PDF]
Journal of Agricultural MachineryRobotic harvesting in agriculture is an effective method for producing healthy fruit, reducing costs, and increasing productivity. Detecting and harvesting sweet peppers, however, remains a challenging task.
O. Doosti Irani +2 more
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Yield Estimation Method of Apple Tree Based on Improved Lightweight YOLOv5
智慧农业, 2021 Yield estimation of fruit tree is one of the important works in orchard management. In order to improve the accuracy of in-situ yield estimation of apple trees in orchard, a method for the yield estimation of single apple tree, which includes an improved
LI Zhijun +4 more
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FRUIT RIPENESS DETECTION USING DEEP LEARNING
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT, 2023 Abstract—The agricultural industry has been facing challenges in traditional and manual visual grading of fruits due to its laborious nature and inconsistent inspection and classification process. To accurately estimate yield and automate harvesting, it is crucial to classify the fruits based on their ripening stages.
LINGAMGUNTA ASRITHA +3 more
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Frontiers in Plant Science, 2022 As one of the representative algorithms of deep learning, a convolutional neural network (CNN) with the advantage of local perception and parameter sharing has been rapidly developed. CNN-based detection technology has been widely used in computer vision,
Chenglin Wang +9 more
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