Soil classification through ai techniques

Registration ID: IJNRD_189729

Published ID: IJNRD2303464

DOI: Click Here to Get

Chilakala david , Kaleru likhitha , Patlolla ruchitha

Agricultural, land type, SVM technique, image processing, and classification techniques.

A vital element in agriculture is soil. There are numerous varieties of soil. Many types of soil support a wide range of crops, and each type of soil has unique qualities. Understanding the qualities and characteristics of various soil types is necessary to determine which crops thrive in particular soil types. Machine learning techniques might prove helpful in this situation. In recent years, it has undergone substantial development. Machine learning is still a very young and challenging research area in agricultural data processing. The conventional procedures for classifying soil in a laboratory take a lot of time, work, and money. In this, we created a model that predicts the red soil type from other soils using convolutional neural networks. Our strategy entails creating a model to determine whether or not red dirt is present in an image when the user delivers the input image. Image pre-processing, feature extraction, and classification are a few of the processes that make up the process of detecting and classifying red dirt.

Published Paper   E-Certificate

Chilakala david, Kaleru likhitha, & Patlolla ruchitha (March-2023). Soil classification through ai techniques. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(3), e506-e515. https://ijnrd.org/papers/IJNRD2303464.pdf

Volume 8 Issue 3, March-2023

Pages : e506-e515

Paper Reg. ID: IJNRD_189729

Published Paper Id: IJNRD2303464

Downloads: 000121157

Research Area: Computer Science & Technology 

Country: KHAMMAM, TELANGANA, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2303464.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2303464

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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