Machine Learning Based Plant Leaf Disease Detection and Severity Assessment Techniques: State-of-the-Art

2017 ◽  
pp. 199-226 ◽  
Author(s):  
Pragati Pukkela ◽  
Surekha Borra
Keyword(s):  
Machine Learning ◽  
State Of The Art ◽  
Disease Detection ◽  
Severity Assessment ◽  
Plant Leaf ◽  
Leaf Disease ◽  
Assessment Techniques

scholarly journals DETECTION OF PLANT LEAF DISEASES IN AGRICULTURE USING RECENT IMAGE PROCESSING TECHNIQUES – A REVIEW

2019 ◽  
Vol 7 (1) ◽  
pp. 29-33
Author(s):  
Arpan Singh Rajput ◽  
Shailja Shukla ◽  
S. S. Thakur
Keyword(s):  
Image Processing ◽  
State Of The Art ◽  
Disease Classification ◽  
Disease Detection ◽  
Plant Leaf ◽  
Leaf Disease ◽  
Processing Techniques ◽  
Large Work ◽  
Respective Product ◽  
Automatic Technique

Purpose: Agricultural productivity is something on which the economy highly depends in India as well in all over the world. India is an agriculture-dependent country; wherein about 70% of the population depends on agriculture. Methodology: This is one of the main reasons that disease detection in agriculture plays an important role, as having the disease in plant leaf is quite natural. If proper observations are not taken in the agriculture field then it causes serious effects on plants due to which respective product quality and productivity are affected. Detection of plant leaf disease through effective and accurate automatic technique is beneficial at the starting stage as it reduces a large work of monitoring in big farms of crops. Result: This paper presents the review on the state of the art disease classification techniques presently used using image processing that can be used for plant leaf disease detection in agriculture.

Performance of deep learning vs machine learning in plant leaf disease detection

2021 ◽  
Vol 80 ◽  
pp. 103615
Author(s):  
R. Sujatha ◽  
Jyotir Moy Chatterjee ◽  
NZ Jhanjhi ◽  
Sarfraz Nawaz Brohi
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Disease Detection ◽  
Plant Leaf ◽  
Leaf Disease

House Plant Leaf Disease Detection and Classification Using Machine Learning

2022 ◽  
pp. 17-26
Author(s):  
Bhimavarapu Usharani
Keyword(s):  
Machine Learning ◽  
Blood Pressure ◽  
Bacterial Infections ◽  
Clustering Algorithm ◽  
Disease Detection ◽  
Diseased Leaf ◽  
Lower Body ◽  
Linear Classification ◽  
Plant Leaf ◽  
Leaf Disease

Hibiscus is a fantastic herb, and in Ayurveda, it is one of the most renowned herbs that have extraordinary healing properties. Hibiscus is rich in vitamin C, flavonoids, amino acids, mucilage fiber, moisture content, and antioxidants. Hibiscus can help with weight loss, cancer treatment, bacterial infections, fever, high blood pressure, lower body temperature, treat heart and nerve diseases. Automatic leaf disease detection is an essential task. Image processing is one of the popular techniques for the plant leaf disease detection and categorization. In this chapter, the diseased leaf is identified by concurrent k-means clustering algorithm and then features are extracted. Finally, reweighted KNN linear classification algorithms have been used to detect the diseased leaves categories.

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