Computer vision technology in agricultural automation —A review
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TLDR
It is found that the existing technology can help the development of agricultural automation for small field farming to achieve the advantages of low cost, high efficiency and high precision, but there are still major challenges.About:
This article is published in Information Processing in Agriculture.The article was published on 2020-03-01 and is currently open access. It has received 228 citations till now.read more
Citations
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Machine Learning Applications for Precision Agriculture: A Comprehensive Review
TL;DR: In this paper, the authors present a systematic review of ML applications in the field of agriculture, focusing on prediction of soil parameters such as organic carbon and moisture content, crop yield prediction, disease and weed detection in crops and species detection.
Journal ArticleDOI
Visual Perception Enabled Industry Intelligence: State of the Art, Challenges and Prospects
TL;DR: The previous research and application of visual perception in different industrial fields such as product surface defect detection, intelligent agricultural production, intelligent driving, image synthesis, and event reconstruction are reviewed.
Journal ArticleDOI
Industry 4.0 Disruption and Its Neologisms in Major Industrial Sectors: A State of the Art
Ocident Bongomin,Aregawi Yemane,Brendah Kembabazi,Clement Malanda,Mwewa Chikonkolo Mwape,Nonsikelelo Sheron Mpofu,Dan Tigalana,Dan Tigalana +7 more
TL;DR: In this paper, a study aimed at identifying industry 4.0 neologisms and illustrating the convergence of 12 disruptive technologies including 3D printing, artificial intelligence, augmented reality, big data, blockchain, cloud computing, drones, Internet of Things, nanotechnology, robotics, simulation, and synthetic biology in agriculture, healthcare, and logistics industries was illustrated.
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Exploring the relationship between ICT, SCM practices and organizational performance in agri-food supply chain
TL;DR: In this article, the role of information and communication technology (ICT) in agri-food supply chain and determines the impact of supply chain management (SCM) practices on firm performance.
Journal ArticleDOI
Robotic Aubergine Harvesting Using Dual-Arm Manipulation
TL;DR: A dual-arm aubergine harvesting robot consisting of two robotic arms configured in an anthropomorphic manner to optimize the dual workspace is presented, which enables the simultaneous harvesting of two aubergines and a collaborative behavior between the arms to solve occlusions.
References
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TL;DR: Wang et al. as discussed by the authors investigated factors influencing intent to adopt unmanned aerial vehicles for use in agricultural operations in Jilin Province, China, and used probit analysis to estimate the influence of factors on intent to use UAVs for plant protection application operations.
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Detection of soybean aphids in a greenhouse using an image processing technique
Mohammadmehdi Maharlooei,Saravanan Sivarajan,Sreekala G. Bajwa,Jason P. Harmon,John Nowatzki +4 more
TL;DR: The results showed that images captured with an inexpensive regular digital camera gave satisfactory results under high illumination conditions, and the misclassification percentage was low for most cameras with different resolutions under high illuminated conditions.
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Validation of agronomic UAV and field measurements for tomato varieties
Juan Enciso,Carlos A. Avila,Jinha Jung,S. Elsayed-Farag,Anjin Chang,Junho Yeom,Juan Landivar,Murilo M. Maeda,Jose C. Chavez +8 more
TL;DR: In the future, UAV crop growth and NDVI monitoring could be improved through temporally dense data acquisition, increasing the number of ground samples and their geometric coincidence with the grids in UAV images, removal of weather effects, and other systematic errors caused from image quality and grid size.
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Automatic delivery and recovery system of Wireless Sensor Networks (WSN) nodes based on UAV for agricultural applications
Fan Ouyang,Hui Cheng,Yubin Lan,Yali Zhang,Xuanchun Yin,Jie Hu,Peng Xiaodong,Guobin Wang,Shengde Chen +8 more
TL;DR: An UAV-based scheme for automatic delivery and recovery of WSN nodes in the field, which includes a combination of specially designed UAV, node platforms together with a GNSS-RTK (Global Navigation Satellite System, Real – Time Kinematic) system is proposed.
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Towards real-time crops surveillance for disease classification: exploiting parallelism in computer vision
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