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Application of Vision Technology and Artificial Intelligence in Smart Farming

Author

Listed:
  • Xiuguo Zou

    (College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, China
    Faculty of Applied Science, University of British Columbia, Kelowna, BC V1V 1V7, Canada)

  • Zheng Liu

    (Faculty of Applied Science, University of British Columbia, Kelowna, BC V1V 1V7, Canada)

  • Xiaochen Zhu

    (School of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China)

  • Wentian Zhang

    (Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW 2007, Australia)

  • Yan Qian

    (College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, China)

  • Yuhua Li

    (College of Artificial Intelligence, Nanjing Agricultural University, Nanjing 210031, China)

Abstract

With the rapid advancement of technology, traditional farming is gradually transitioning into smart farming [...]

Suggested Citation

  • Xiuguo Zou & Zheng Liu & Xiaochen Zhu & Wentian Zhang & Yan Qian & Yuhua Li, 2023. "Application of Vision Technology and Artificial Intelligence in Smart Farming," Agriculture, MDPI, vol. 13(11), pages 1-4, November.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:11:p:2106-:d:1275107
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    References listed on IDEAS

    as
    1. Xinyi He & Qiyang Cai & Xiuguo Zou & Hua Li & Xuebin Feng & Wenqing Yin & Yan Qian, 2023. "Multi-Modal Late Fusion Rice Seed Variety Classification Based on an Improved Voting Method," Agriculture, MDPI, vol. 13(3), pages 1-16, March.
    2. Guanjie Jiao & Xiawei Shentu & Xiaochen Zhu & Wenbo Song & Yujia Song & Kexuan Yang, 2022. "Utility of Deep Learning Algorithms in Initial Flowering Period Prediction Models," Agriculture, MDPI, vol. 12(12), pages 1-17, December.
    3. Yifang Ren & Fenghua Ling & Yong Wang, 2023. "Research on Provincial-Level Soil Moisture Prediction Based on Extreme Gradient Boosting Model," Agriculture, MDPI, vol. 13(5), pages 1-17, April.
    4. Naimin Xu & Guoxiang Sun & Yuhao Bai & Xinzhu Zhou & Jiaqi Cai & Yinfeng Huang, 2023. "Global Reconstruction Method of Maize Population at Seedling Stage Based on Kinect Sensor," Agriculture, MDPI, vol. 13(2), pages 1-15, January.
    5. Jie Ding & Cheng Zhang & Xi Cheng & Yi Yue & Guohua Fan & Yunzhi Wu & Youhua Zhang, 2023. "Method for Classifying Apple Leaf Diseases Based on Dual Attention and Multi-Scale Feature Extraction," Agriculture, MDPI, vol. 13(5), pages 1-19, April.
    6. Hongyun Hao & Peng Fang & Wei Jiang & Xianqiu Sun & Liangju Wang & Hongying Wang, 2022. "Research on Laying Hens Feeding Behavior Detection and Model Visualization Based on Convolutional Neural Network," Agriculture, MDPI, vol. 12(12), pages 1-12, December.
    7. Hong Gu Lee & Min-Jee Kim & Su-bae Kim & Sujin Lee & Hoyoung Lee & Jeong Yong Sin & Changyeun Mo, 2023. "Identifying an Image-Processing Method for Detection of Bee Mite in Honey Bee Based on Keypoint Analysis," Agriculture, MDPI, vol. 13(8), pages 1-17, July.
    8. Yong Li & Hebing Liu & Jialing Wei & Xinming Ma & Guang Zheng & Lei Xi, 2023. "Research on Winter Wheat Growth Stages Recognition Based on Mobile Edge Computing," Agriculture, MDPI, vol. 13(3), pages 1-16, February.
    9. Jinkai Guo & Xiao Xiao & Jianchi Miao & Bingquan Tian & Jing Zhao & Yubin Lan, 2023. "Design and Experiment of a Visual Detection System for Zanthoxylum-Harvesting Robot Based on Improved YOLOv5 Model," Agriculture, MDPI, vol. 13(4), pages 1-18, March.
    10. Yongzhe Sun & Zhixin Zhang & Kai Sun & Shuai Li & Jianglin Yu & Linxiao Miao & Zhanguo Zhang & Yang Li & Hongjie Zhao & Zhenbang Hu & Dawei Xin & Qingshan Chen & Rongsheng Zhu, 2023. "Soybean-MVS: Annotated Three-Dimensional Model Dataset of Whole Growth Period Soybeans for 3D Plant Organ Segmentation," Agriculture, MDPI, vol. 13(7), pages 1-19, June.
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