scholarly journals Survey Paper on Detection of Unhealthy Region of Plant Leaves Using Image Processing and Soft Computing Techniques

Author(s):  
Namita M. Butale ◽  
Dattatraya V Kodavade
2015 ◽  
Vol 81 (5-8) ◽  
pp. 771-778 ◽  
Author(s):  
Pascual Noradino Montes Dorantes ◽  
Marco Aurelio Jiménez Gómez ◽  
Gerardo Maximiliano Méndez ◽  
Juan Pablo Nieto González ◽  
Jesús de la Rosa Elizondo

Author(s):  
Vivek K. Verma ◽  
Tarun Jain

The disease occurrence phenomena in plants are season-based which is dependent on the presence of the pathogen, crops, environmental conditions, and varieties grown. Some plant varieties are particularly subject to outbreaks of diseases; on the other hand, some are opposite to them. Huge numbers of diseases are seen on the plant leaves and stems. Diseases management is a challenging task. Generally, diseases are seen on the leaves or stems of the plant. Image processing is the best way for the detection of plant leaf diseases. Different kinds of diseases occur because of the attack of bacteria, fungi, and viruses. The monitoring of leaf area is an important tool in studying physiological capabilities associated with plant boom. Plant disorder is usually an unusual growth or dysfunction of a plant. Sometimes diseases damage the leaves of plants.


2014 ◽  
Vol 6 (2) ◽  
pp. 65-80 ◽  
Author(s):  
J. Premaladha ◽  
S. Sujitha ◽  
M. Lakshmi Priya ◽  
K.S. Ravichandr

2016 ◽  
Vol 78 (10) ◽  
Author(s):  
Sharmila Banu Kather ◽  
BK Tripathy

Spatial data analysis is being used efficiently and the governments have realized that georeferenced data yields more insight with time and locations. Epidemiology is about the study of origin and distribution of diseases and dates back to the 1600s with the instance of cholera in London. Data Science has been evolving and when analyzed with Soft Computing techniques like Rough Set Theory (RST), Fuzzy Sets, Granulation Computing which encompasses the data in its original nature, results can be obtained with accrued accuracy. This survey paper highlights Spatial Data Mining methods used in the field of Epidemiology, identifies crucial challenges and discusses of the use of Soft Computing methods. 


2019 ◽  
Vol 23 (6) ◽  
pp. 1777-1778 ◽  
Author(s):  
Irina Perfilieva ◽  
Javier Montero ◽  
Salvatore Sessa

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