Results 11 to 20 of about 1,269,196 (287)
Mango Fruit Load Estimation Using a Video Based MangoYOLO—Kalman Filter—Hungarian Algorithm Method
Sensors, 2019 Pre-harvest fruit yield estimation is useful to guide harvesting and marketing resourcing, but machine vision estimates based on a single view from each side of the tree (“dual-view”) underestimates the fruit yield as fruit can be hidden from
Zhenglin Wang +2 more
doaj +3 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
Physiological and biochemical changes in imported litchi fruit [PDF]
, 2010 It is important to determine the appropriate conditions for maintaining postharvest quality of litchi fruit after arrival from overseas markets. The present study, therefore, aimed to detail the effects of different storage conditions on physiological ...
Somboonkaew, Nettra
core +6 more sources
Fast Recognition and Counting Method of Dragon Fruit Flowers and Fruits Based on Video Stream
Sensors, 2023 Dragon fruit (Hylocereus undatus) is a tropical and subtropical fruit that undergoes multiple ripening cycles throughout the year. Accurate monitoring of the flower and fruit quantities at various stages is crucial for growers to estimate yields, plan orders, and implement effective management strategies.
Li, Xiuhua +5 more
openaire +3 more sources
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.
null Romil Mahajan +4 more
openaire +1 more source
Location of Fruits by Counting: A Point-to-Point Approach
Agronomy, 2022 The emergence of deep learning-based methods for harvesting and yield estimates, including object detection or image segmentation-based methods, has notably improved performance but has also resulted in large annotation workloads. Considering the difficulty of such annotation, a method for locating fruit is developed in this study using only center ...
Bo Li, Cheng Chen
openaire +2 more sources
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 +1 more source
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.
Afonso, Manya +7 more
openaire +4 more sources
Regulation of tomato fruit ripening [PDF]
, 2009 Fruit ripening is a sophisticatedly orchestrated developmental process, unique to plants, that results in major physiological and metabolic changes, ultimately leading to fruit decay and seed dispersal. Because of their strong impact on fruit nutritional
Regad, Farid +9 more
core +1 more source
Postharvest quality of conventionally and organically grown banana fruit [PDF]
, 2001 Quality is increasingly important for retailers, who tend to look for more definitive assessment criteria. Taste has become a major issue over past years for consumers, who are seeking higher quality produce. For banana fruit, at least one major retailer
Caussiol, Laure
core +4 more sources