Deep Learning Applications in Agriculture: The Role of Deep Learning in Smart Agriculture

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Author(s): Hari Kishan Kondaveeti (VIT-AP University, Andhra Pradesh, India), Gonugunta Priyatham Brahma (VIT-AP University, Andhra Pradesh, India)and Dandhibhotla Vijaya Sahithi (VIT-AP University, Andhra Pradesh, India)
Copyright: 2021
Pages: 21
Source title: Artificial Intelligence and IoT-Based Technologies for Sustainable Farming and Smart Agriculture
Source Author(s)/Editor(s): Pradeep Tomar (Gautam Buddha University, India)and Gurjit Kaur (Delhi Technological University, India)
DOI: 10.4018/978-1-7998-1722-2.ch020

Keywords: Agricultural and Food Technologies / Artificial Intelligence / Computer Science & IT / Information Science Reference

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Abstract

Deep learning (DL), a part of machine learning (ML), comprises a contemporary technique for processing the images and analyzing the big data with promising outcomes. Deep learning methods are successfully being used in various sectors to gain better results. Agriculture sector is one of the sectors that could be benefitted from the deep learning techniques since the current agriculture techniques cannot keep up with the rapid growth in population. In this chapter, the recent trends in the applications of deep learning techniques in the agricultural sector and the survey of the research efforts that employ deep learning techniques are going to be discussed. Also, the models that are implemented are going to be analyzed and compared with the other existing models.

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Deep Learning Applications in Agriculture: The Role of Deep Learning in Smart Agriculture

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