Abstract
SHS investigation development is considered from the geographical and historical viewpoint. 3 stages are described. Within Stage 1 the work was carried out in the Department of the Institute of Chemical Physics in Chernogolovka where the scientific discovery had been made. At Stage 2 the interest to SHS arose in different cities and towns of the former USSR. Within Stage 3 SHS entered the international scene. Now SHS processes and products are being studied in more than 50 countries.
Abstract
Rice is the staple food crop of a large population spread worldwide, today
and in the past. Millions of people are dependent on rice for an active and healthy
lifestyle. A smart and sustainable world is a pictograph that will come into reality with
an abundance of quality food for humankind. Smart precision agriculture leading to the
fulfillment of high-quality food is a challenge for many researchers. In the same series
of thoughts, this chapter proposes a Smart App using Deep Learning that helps
diagnose the rice crop disease to avoid failure of the crop. This chapter demonstrates an
easy to handle, farmer-friendly mobile app, with the help of which farmers can take
pictures of crop leaves as soon as some abnormality is observed. The app may then
analyse the crop leaf image to predict the probability of suspected disease, which gives
the farmer indication of loss and helps them take necessary preventive measures.
Keywords:
Convolution Neural Network, Crop Disease Detection, Data augmentation, Deep Learning, Rice, Smart app.
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Authors:Bentham Science Books