scholarly journals Feature Selection and Performance Improvement of Malware Detection System using Cuckoo Search Optimization and Rough Sets

2020 ◽  
Vol 11 (5) ◽  
Author(s):  
Ravi Kiran Varma P ◽  
PLN Raju ◽  
K V ◽  
Akhila Kalidindi
Keyword(s):  
Feature Selection ◽  
Performance Improvement ◽  
Rough Sets ◽  
Detection System ◽  
Malware Detection ◽  
Cuckoo Search ◽  
Search Optimization ◽  
Cuckoo Search Optimization ◽  
And Performance

scholarly journals Leukaemia Detection in Microscopic Imagery using Optimization Algorithm

2018 ◽  
Vol 7 (2.24) ◽  
pp. 299
Author(s):  
M Venkata Dasu ◽  
P Subbaiah
Keyword(s):  
Cancer Detection ◽  
Optimization Algorithm ◽  
Detection System ◽  
Cuckoo Search ◽  
Scale Invariant ◽  
Blood Cancer ◽  
Segmented Image ◽  
Search Optimization ◽  
Cuckoo Search Optimization ◽  
Scale Invariant Feature

In this paper, automated approach of blood cancer detection is proposed. Usually microscopic images examined by experts manually are time consuming and less accuracy. The automated blood cancer detection system analyses the microscopic image and overcomes these drawbacks. The proposed system extracts the features of the image and applies filtering techniques. In this paper proposed method is cuckoo search optimization algorithm which is used in line with segmentation. The features of segmented image can be obtained from Scale invariant feature transform. Some of the features like PSNR, sensitivity, accuracy, etc. are calculated for leukemia detection. The performance is compared with the existing method ACO. The proposed system is tested on image dataset and 94.24% accuracy is achieved. The proposed system is successfully implemented in MATLAB. 

scholarly journals A Novel Sentimental Analysis using Optimized Relevance Vector Machine Classifier

2018 ◽  
Vol 7 (4.7) ◽  
pp. 164
Author(s):  
N. Saranya ◽  
R. Gunavathi ◽  
. .
Keyword(s):  
Machine Learning ◽  
Cuckoo Search ◽  
Relevance Vector Machine ◽  
Sentiment Classification ◽  
Search Optimization ◽  
Cuckoo Search Optimization ◽  
And Performance

Sentimental analysis is the process of identifying the human’s thoughts or feelings. So Many methods have been developed for the sentimental analysis. Machine learning is one of the widely used approaches towards sentiment classification. In this work, Sentimental analysis is done by using Relevance Vector Machine Classifier with Cuckoo Search Optimization. Here Relevance Vector Machine Classifier (RVMC) is combined with Cuckoo Search Optimization (CSO) for better accuracy and performance. Experiment is made with movie and twitter datasets. Accuracy, precision and recall of all other techniques are evaluated. Here the comparison is made among other algorithms. The result shows that RVMC-CSO algorithm gives accuracy and good performance than other algorithm like SVM, ELM and RVM.  

A new technique for guided filter based image denoising using modified cuckoo search optimization

2021 ◽  
Vol 176 ◽  
pp. 114884
Author(s):  
Himanshu Singh ◽  
Sethu Venkata Raghavendra Kommuri ◽  
Anil Kumar ◽  
Varun Bajaj
Keyword(s):  
Image Denoising ◽  
Cuckoo Search ◽  
New Technique ◽  
Guided Filter ◽  
Search Optimization ◽  
Cuckoo Search Optimization ◽  
A New Technique
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