Validation of data preprocessing to guarantee high accuracy in deep learning treatments: Agricultural domain as a case of study
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Date
2023-06-06
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Publisher
university of eloued جامعة الوادي
Abstract
The agricultural sector occupies a great importance to mankind, and it is constantly
striving to strengthen and develop its systems. Similar to other fields, the agricultural
industry has adopted deep learning techniques to process agricultural data, with the aim
of achieving high quality crop results. In different regions as Europe, North America, and
East Asia, these techniques have been used to identify plant diseases, their causes, and
even predict crop yields in certain seasons. However, we have noticed a lack of interest in
applying these technologies in the desert environment, because it is completely different
in terms of non-fertile soil quality, drought, water salinity, extreme temperatures, and so
on. Given the above conditions, we propose to use previously developed models based
on convolutional neural networks to solve the aforementioned problems. Our focus is to
identify and classify tomato leaf diseases using a specially collected dataset from a desert
environment.
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Description
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Keywords
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