CONVOLUTIONAL NEURAL NETWORK BASED CROP IDENTIFICATION

Authors:

BodakuntlaNagamani Kumar, Balla Ranjith Kumar, Gattu Pranay Kumar, Dr.Punyaban Patel

Page No: 1-7

Abstract:

Plants are the most important and primary food resource of many living things like humans, birds, animals, insects, etc. Owing to the increasing world population and decreasing food resources, nature forces us to improve the efficiency in the agricultural fields. Many Modern Computing Technologies are emerged and are get implemented in various domains of agriculture. We know that there are numerous types of plant species available on the earth. Identifying the name of those plants manually is time consuming. Automating this using a Classification algorithm will help Biologists, environmentalists, etc. in various ways. This paper presents Convolutional Neural Network based crop identification. Agriculture Crop Images from the Kaggle dataset has been used as the primary resource of data. Our experimental results have demonstrated that Convolutional Neural Network classification model can achieve very competitive results on both the Accuracy (97.5%) and Precision (97.1%) for crop species identification.

Description:

Plant species, Convolutional Neural Network, Biologists, deep learningAccuracy.

Volume & Issue

Volume-12,Issue-4

Keywords

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