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Computer vision technology in agricultural automation--A review 被引量:23
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作者 hongkun tian tianhai Wang +2 位作者 Yadong Liu Xi Qiao Yanzhou Li 《Information Processing in Agriculture》 EI 2020年第1期1-19,共19页
Computer vision is a field that involves making a machine “see”.This technology uses a camera and computer instead of the human eye to identify,track and measure targets for further image processing.With the develop... Computer vision is a field that involves making a machine “see”.This technology uses a camera and computer instead of the human eye to identify,track and measure targets for further image processing.With the development of computer vision,such technology has been widely used in the field of agricultural automation and plays a key role in its development.This review systematically summarizes and analyzes the technologies and challenges over the past three years and explores future opportunities and prospects to form the latest reference for researchers.Through the analyses,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.However,there are still major challenges.First,the technology will continue to expand into new application areas in the future,and there will be more technological issues that need to be overcome.It is essential to build large-scale data sets.Second,with the rapid development of agricultural automation,the demand for professionals will continue to grow.Finally,the robust performance of related technologies in various complex environments will also face challenges.Through analysis and discussion,we believe that in the future,computer vision technology will be combined with intelligent technology such as deep learning technology,be applied to every aspect of agricultural production management based on large-scale datasets,be more widely used to solve the current agricultural problems,and better improve the economic,general and robust performance of agricultural automation systems,thus promoting the development of agricultural automation equipment and systems in a more intelligent direction. 展开更多
关键词 Computer vision Image processing Agricultural automation Intelligent detection
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Novel boron-and sulfur-doped polycyclic aromatic hydrocarbon as multiple resonance emitter for ultrapure blue thermally activated delayed fluorescence polymers
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作者 Fan Chen Lei Zhao +7 位作者 Xingdong Wang Qingqing Yang Weili Li hongkun tian Shiyang Shao Lixiang Wang Xiabin Jing Fosong Wang 《Science China Chemistry》 SCIE EI CAS CSCD 2021年第4期547-551,共5页
Boron(B)-and sulfur(S)-doped polycyclic aromatic hydrocarbons(PAHs)are developed as a novel kind of multiple resonance emitters for ultrapure blue thermally activated delayed fluorescence(TADF)polymers with narrowband... Boron(B)-and sulfur(S)-doped polycyclic aromatic hydrocarbons(PAHs)are developed as a novel kind of multiple resonance emitters for ultrapure blue thermally activated delayed fluorescence(TADF)polymers with narrowband electroluminescence.The combination of electron-deficient B atom and electron-rich S atom in PAH can form an intramolecular push-pull electronic system in a rigid aromatic framework,leading to reduced singlet-triplet energy splitting and limited structure relaxation of excited states.The critical roles of S atom in determining emission properties with respect to the oxygen analogues are in two aspects:(i)reducing energy bandgap to shift emission from human-eye-insensitive ultraviolet zone to blue region,and(ii)promoting reverse intersystem crossing process by heavy-atom effect to activate TADF effect.The resulting polymer containing B,S-doped PAH as emitter and acridan as host exhibits efficient blue electroluminescence at 458 nm with small full-width at halfmaximum of 31 nm,representing the first example for ultrapure TADF polymer with narrowband electroluminescence. 展开更多
关键词 polycyclic aromatic hydrocarbon BORON SULFUR multiple resonance thermally activated delayed fluorescence
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