Image Pre-Processing and Paddy Pests Detection Using Tensorflow

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Author(s): Rahul Sharma (Lovely Professional University, India)and Amar Singh (Lovely Professional University, India)
Copyright: 2021
Pages: 9
Source title: Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease
Source Author(s)/Editor(s): Manikant Roy (Lovely Professional University, India)and Lovi Raj Gupta (Lovely Professional University, India)
DOI: 10.4018/978-1-7998-7188-0.ch010

Keywords: Knowledge Management and Library Science / Machine Learning / Medical Information Science Reference / Medical Technologies

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Abstract

Agriculture is one of the important sources of earning worldwide. With the rapid expansion of the human population and food security for all, the agriculture sector needs to be boosted to increase the yield. Agriculture is the prime source of livelihood in India for more than 50% of the total population. As per Indian agriculture and allied industries industry report, agriculture is one of the major contributors in gross value. Agricultural crops suffer heavy losses due to insect damage and plant diseases. Worldwide, out of the crop losses, major losses are caused by plant pests. In this chapter, various image pre-processing methods and the need of pre-preprocessing are discussed in detail. For image classification, TensorFlow deep neural network is presented. Deep learning model is used for automatic and early detection of paddy pests. Early detection of the pests will aid farmers in adopting necessary preventive measures. Multiple ways to reduce overfitting during model training are also suggested.

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