Plant Detection Using Unmanned Drone via Convolution Neural Network

Authors

  • P. Geetha Department of Computer Science and Engineering, Cambridge Institute of Technology, Bangalore, India
  • Siddharth Singh Department of Computer Science and Engineering, Cambridge Institute of Technology, Bangalore, India
  • K. V. Sreeram Department of Computer Science and Engineering, Cambridge Institute of Technology, Bangalore, India
  • Kamalesh Parmar Department of Computer Science and Engineering, Cambridge Institute of Technology, Bangalore, India
  • Kumar Abhinav Department of Computer Science and Engineering, Cambridge Institute of Technology, Bangalore, India

Keywords:

CNN, neural network, plants, image detection, unmanned

Abstract

Plants are essential resources for nature and people’s lives. Plant recognition provides valuable information for plant research and development, and has great impact on environmental protection and exploration. Species knowledge is important for shielding biodiversity. The identification of plants by conventional keys is complex, time consuming, and thanks to the utilization of specific botanical terms frustrating for non-experts. This creates a tough to beat hurdle for novices curious about acquiring species knowledge. Today, there's an increasing interest in automating the method of species identification. Convolutional neural networks are a well-liked realm of machine learning, and are often used for image classification, as during this paper.

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Published

28-05-2021

How to Cite

[1]
P. Geetha, S. Singh, K. V. Sreeram, K. Parmar, and K. Abhinav, “Plant Detection Using Unmanned Drone via Convolution Neural Network”, IJRESM, vol. 4, no. 5, pp. 153–155, May 2021.

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Articles