Developing Machine Vision in Tree-Fruit Applications—Fruit Count, Fruit Size and Branch Avoidance in Automated Harvesting [PDF]
SensorsRecent developments in affordable depth imaging hardware and the use of 2D Convolutional Neural Networks (CNN) in object detection and segmentation have accelerated the adoption of machine vision in a range of applications, with mainstream models often ...
Chiranjivi Neupane +3 more
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Honey bee hives decrease wild bee abundance, species richness, and fruit count on farms regardless of wildflower strips [PDF]
Scientific Reports, 2021 Pollinator refuges such as wildflower strips are planted on farms with the goals of mitigating wild pollinator declines and promoting crop pollination services.
G. M. Angelella +2 more
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On Tree Mango Fruit Detection and Counting System
International Journal of Next-Generation Computing, 2023 For yield estimation, it is crucial to achieve quick and precise identification of mango fruits in the natural situations and surroundings. Using imaging with computer vision to accurately detect and count fruits during plant growth is important.
Romil Mahajan +4 more
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Weakly Supervised Fruit Counting for Yield Estimation Using Spatial Consistency [PDF]
IEEE Robotics and Automation Letters, 2019 https://youtu.be ...
Enrico Bellocchio +3 more
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An Intelligent Method for Fruit Counting System
Journal of Advance Research in Social Science and Humanities (ISSN: 2208-2387), 2015 In this paper image processing based yield counting system and health monitoring of citrus fruit is being processed. The model which is explained in the paper can be worked in any graphical area. The system consists of an automatic robot which revolves around. The axis of citrus tree and clicks various images from different angle.
Sushil V. Atone +2 more
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Deep Count: Fruit Counting Based on Deep Simulated Learning [PDF]
Sensors, 2017 Recent years have witnessed significant advancement in computer vision research based on deep learning. Success of these tasks largely depends on the availability of a large amount of training samples. Labeling the training samples is an expensive process.
Maryam Rahnemoonfar, Clay Sheppard
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Culling Double Counting in Sequence Images for Fruit Yield Estimation [PDF]
Agronomy, 2022 Exact yield estimation of fruits on plants guaranteed fine and timely decisions on harvesting and marketing practices. Automatic yield estimation based on unmanned agriculture offers a viable solution for large orchards. Recent years have witnessed notable progress in computer vision with deep learning for yield estimation. Yet, the current practice of
Xue Xia +5 more
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Tomato Fruit Detection and Counting in Greenhouses Using Deep Learning [PDF]
Frontiers in Plant Science, 2020 Accurately detecting and counting fruits during plant growth using imaging and computer vision is of importance not only from the point of view of reducing labor intensive manual measurements of phenotypic information, but also because it is a critical step toward automating processes such as harvesting.
Manya Afonso +7 more
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Comparative transcriptomic analysis identifies genes responsible for fruit count and oil yield in the oil tea plant Camellia chekiangoleosa. [PDF]
Sci Rep, 2018 Xie Y, Wang X.
europepmc +3 more sources
Short Notes: Application of Vesicular Arbuscular Mycorrhiza: Increasing the Yield of Okra
Maǧallaẗ al-baṣraẗ al-ʻulūm al-zirāʻiyyaẗ, 2023 A commercially available arbuscular mycorrhizal fungi was applied to investigate the response of okra plants, particularly the yield components. Okra plants were separately treated with inorganic fertilizer, organic fertilizer, and mycorrhiza.
Maricar O. Dahilig +1 more
doaj +5 more sources