Tomato Leaf Diseases Identification using CNN

Dhulipalla Srija; DEVARAKONDA AKSHAYA; BALATHOTI ANUPRIYA

Tomato Leaf Diseases Identification using CNN

June 2022

Vol-8, Issue-3

Paper ID: 17300

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

INFORMATION TECHNOLOGY

Keywords

Deep Learning Tomato Leaves Disease Detection

Abstract

Crop diseases are key danger to food security. The speedy identification of the diseases are still difficult in many proportions of the world. This is because of lack of proper infrastructure. Now a days smart phone usage is increased and computer vision technology is also increased. Because of this smartphone assisted disease identification is possible using Deep Learning. we are developing web application to identify the disease of leaf using CNN. Public dataset contains 10000 images contains both infected and healthy tomato leaves. They are collected under controlled conditions. In the proposed method deep learning is used to detect the disease of the leaves. A deep convolutional neural network model is trained to identify these diseases. In this we have used inception v3 model. The trained achieved 88.34% accuracy on the test dataset. This method is more feasible to detect the diseases in tomato leaves.

License

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Author Information

#	Name	Institute / Affiliation
1	Dhulipalla Srija	VASIREDDY VENKATADRI INSTITUTE OF TECHNOLOGY
2	DEVARAKONDA AKSHAYA	VASIREDDY VENKATADRI INSTITUTE OF TECHNOLOGY
3	BALATHOTI ANUPRIYA	VASIREDDY VENKATADRI INSTITUTE OF TECHNOLOGY

How to Cite

Use the following formats to cite this article in your research.

APA Style

Srija, Dhulipalla, AKSHAYA, DEVARAKONDA, & ANUPRIYA, BALATHOTI (2022). Tomato Leaf Diseases Identification using CNN. International Journal of Advance Research and Innovative Ideas In Education, 8(3), 4232-4238.

MLA Style

Srija, Dhulipalla, et al. "Tomato Leaf Diseases Identification using CNN." International Journal of Advance Research and Innovative Ideas In Education, vol. 8, no. 3, 2022, pp. 4232-4238.

IEEE Style

Dhulipalla Srija, DEVARAKONDA AKSHAYA, and BALATHOTI ANUPRIYA, "Tomato Leaf Diseases Identification using CNN," International Journal of Advance Research and Innovative Ideas In Education, vol. 8, no. 3, pp. 4232-4238, 2022.

Vancouver Style

Srija Dhulipalla, AKSHAYA DEVARAKONDA, ANUPRIYA BALATHOTI. Tomato Leaf Diseases Identification using CNN. International Journal of Advance Research and Innovative Ideas In Education. 2022;8(3):4232-4238.

Harvard Style

Srija, Dhulipalla, AKSHAYA, DEVARAKONDA, & ANUPRIYA, BALATHOTI (2022) 'Tomato Leaf Diseases Identification using CNN', International Journal of Advance Research and Innovative Ideas In Education, 8(3), pp. 4232-4238.

Chicago Style

Srija, Dhulipalla, DEVARAKONDA AKSHAYA, and BALATHOTI ANUPRIYA. "Tomato Leaf Diseases Identification using CNN." International Journal of Advance Research and Innovative Ideas In Education 8, no. 3 (2022): 4232-4238.

Turabian Style

Srija, Dhulipalla, DEVARAKONDA AKSHAYA, and BALATHOTI ANUPRIYA. "Tomato Leaf Diseases Identification using CNN." International Journal of Advance Research and Innovative Ideas In Education 8, no. 3 (2022): 4232-4238.