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Titlebook: Unmanned Aerial Systems in Precision Agriculture; Technological Progre Zhao Zhang,Hu Liu,Yu Jiang Book 2022 The Editor(s) (if applicable) a

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發(fā)表于 2025-3-21 18:36:23 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Unmanned Aerial Systems in Precision Agriculture
副標題Technological Progre
編輯Zhao Zhang,Hu Liu,Yu Jiang
視頻videohttp://file.papertrans.cn/943/942364/942364.mp4
概述Presents the technological progress of UAV applications in precision agriculture, coupled with deep learning.Provides multiple UAV application cases in precision agriculture in Europe and USA.Introduc
叢書名稱Smart Agriculture
圖書封面Titlebook: Unmanned Aerial Systems in Precision Agriculture; Technological Progre Zhao Zhang,Hu Liu,Yu Jiang Book 2022 The Editor(s) (if applicable) a
描述This book, consisting of 8 chapters, describes the state-of-the-art technological progress and applications of unmanned aerial vehicles (UAVs) in precision agriculture. It focuses on the UAV application in agriculture, such as crop disease detection, mid-season yield estimation, crop nutrient status, and high-throughput phenotyping. Different from individual papers focusing on a specific application, this book provides a holistic view for readers with a wide range of subjects. In addition to researchers in the areas of plant science, plant pathology, breeding, engineering, it is also intended for undergraduates and graduates who are interested in imaging processing, artificial intelligence in agriculture, precision agriculture, agricultural automation, and robotics...
出版日期Book 2022
關鍵詞Precision agriculture; Plant health conditions; Crop disease monitoring; Machine learning; Deep learning
版次1
doihttps://doi.org/10.1007/978-981-19-2027-1
isbn_softcover978-981-19-2029-5
isbn_ebook978-981-19-2027-1Series ISSN 2731-3476 Series E-ISSN 2731-3484
issn_series 2731-3476
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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發(fā)表于 2025-3-21 23:01:06 | 只看該作者
Unmanned Aerial Vehicle (UAV) Applications in Cotton Production,ations in cotton production, focusing on field scouting and decision making, such as stand count, growth monitoring, and yield prediction, under different soil, weather conditions, and irrigation management. Meanwhile, the potentials and challenges of using UAV technologies in cotton production are
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地板
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UAV Mission Height Effects on Wheat Lodging Ratio Detection,. The results indicated that the collected images on 91?m (2.5?cm/pixel) mission height could generate a similar or even a little higher detection accuracy over the images collection at 45?m (1.2?cm/pixel) and 15?m (0.4?cm/pixel) height. Comparison of SVM and Resnet50 model results showed that SVM r
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,Corn Goss’s Wilt Disease Assessment Based on UAV Imagery,o classify Goss Wilt severity as a binary issue (i.e., high and low). Two different types of features, including textural (contrast, dissimilarity, homogeneity, angular second moment) and color (hue, saturation, value, lightness, chromatic components: a* and b*, red, green, blue) features were extra
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發(fā)表于 2025-3-22 19:13:32 | 只看該作者
2731-3476 plant pathology, breeding, engineering, it is also intended for undergraduates and graduates who are interested in imaging processing, artificial intelligence in agriculture, precision agriculture, agricultural automation, and robotics...978-981-19-2029-5978-981-19-2027-1Series ISSN 2731-3476 Series E-ISSN 2731-3484
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Sri Charan Kakarla,Lucas Costa,Yiannis Ampatzidis,Zhao Zhang
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發(fā)表于 2025-3-23 07:48:21 | 只看該作者
Zhao Zhang,Cannayen Igathinathane,Paulo Flores,Jithin Mathew,Joel Ransom,Yiannis Ampatzidis,Anup Kum
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