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
doaj +6 more sources
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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Agronomy, 2021 Machine vision from ground vehicles is being used for estimation of fruit load on trees, but a correction is required for occlusion by foliage or other fruits. This requires a manually estimated factor (the reference method).
Anand Koirala +2 more
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Estimation of Fruit Load in Australian Mango Orchards Using Machine Vision
Agronomy, 2021 The performance of a multi-view machine vision method was documented at an orchard level, relative to packhouse count. High repeatability was achieved in night-time imaging, with an absolute percentage error of 2% or less.
Nicholas Todd Anderson +7 more
doaj +3 more sources
Weakly Supervised Fruit Counting for Yield Estimation Using Spatial Consistency [PDF]
IEEE Robotics and Automation Letters, 2019 https://youtu.be ...
Enrico Bellocchio +2 more
exaly +4 more sources
Monocular Camera Based Fruit Counting and Mapping With Semantic Data Association
IEEE Robotics and Automation Letters, 2019 We present a cheap, lightweight, and fast fruit counting pipeline that uses a single monocular camera. Our pipeline that relies only on a monocular camera, achieves counting performance comparable to state-of-the-art fruit counting system that utilizes an expensive sensor suite including LiDAR and GPS/INS on a mango dataset.
Chenhao Liu
exaly +3 more sources
Comparative transcriptomic analysis identifies genes responsible for fruit count and oil yield in the oil tea plant Camellia chekiangoleosa [PDF]
Scientific Reports, 2018 Xuewen Wang, Xie Yun
exaly +2 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
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.
Rahnemoonfar, Maryam, Sheppard, Clay
openaire +3 more sources
Evaluation of methods to estimate understory fruit biomass. [PDF]
PLoS ONE, 2014 Fleshy fruit is consumed by many wildlife species and is a critical component of forest ecosystems. Because fruit production may change quickly during forest succession, frequent monitoring of fruit biomass may be needed to better understand shifts in ...
Marcus A Lashley +4 more
doaj +1 more source