A Review on Microstrip Patch Antenna Performance Improvement Techniques on Various Applications
Volume-3 | Issue-3
A Review on Finding Efficient Approach to Detect Customer Emotion Analysis using Deep Learning Analysis
Volume-3 | Issue-2
A Comparative Analysis of Prediction of Student Results Using Decision Trees and Random Forest
Volume-4 | Issue-3
Study of Security Mechanisms to Create a Secure Cloud in a Virtual Environment with the Support of Cloud Service Providers
Volume-2 | Issue-3
Construction of Black Box to Detect the Location of Road Mishap in Remote Area in the IoT Domain
Volume-3 | Issue-2
Fault Diagnosis in Hybrid Renewable Energy Sources with Machine Learning Approach
Volume-3 | Issue-3
Secure and Optimized Cloud-Based Cyber-Physical Systems with Memory-Aware Scheduling Scheme
Volume-2 | Issue-3
Stochastic Geometry and Performance Analysis of Large Scale Wireless Networks
Volume-3 | Issue-3
Computer Vision on IOT Based Patient Preference Management System
Volume-2 | Issue-2
Fake News Detection using Data Mining Techniques
Volume-3 | Issue-4
A Review on Microstrip Patch Antenna Performance Improvement Techniques on Various Applications
Volume-3 | Issue-3
Fake News Detection using Data Mining Techniques
Volume-3 | Issue-4
A Comparative Analysis of Prediction of Student Results Using Decision Trees and Random Forest
Volume-4 | Issue-3
Speedy Detection Module for Abandoned Belongings in Airport Using Improved Image Processing Technique
Volume-3 | Issue-4
Deployment of Artificial Intelligence with Bootstrapped Meta-Learning in Cyber Security
Volume-4 | Issue-3
Design an Early Detection and Classification for Diabetic Retinopathy by Deep Feature Extraction based Convolution Neural Network
Volume-3 | Issue-2
Design of an Intelligent Approach on Capsule Networks to Detect Forged Images
Volume-3 | Issue-3
Future Challenges of the Internet of Things in the Health Care Domain - An Overview
Volume-3 | Issue-4
Construction of Black Box to Detect the Location of Road Mishap in Remote Area in the IoT Domain
Volume-3 | Issue-2
A Review on Finding Efficient Approach to Detect Customer Emotion Analysis using Deep Learning Analysis
Volume-3 | Issue-2
Volume - 5 | Issue - 1 | march 2023
Published
27 February, 2023
In the current scenario, the death rate due to the cause of skin cancer is increasing enormously. Diagnosis and prediction of Skin Cancer (SC) have become vital at an earlier stage. The main objective of this research is ensemble machine learning with enhanced genetic algorithm technique to achieve higher accuracy in the prediction of skin cancer at an earlier stage compared to other existing techniques. Although many machine learning and deep learning approaches implemented in detecting skin cancer at an earlier stage still there are few limitations. To overcome these problems in our proposed work, the CNN model, ResNet-16 usually produces successful results in extracting the features automatically and classifying the images very accurately. Therefore, the ResNet model used in our work obtains the deep features with the help of a fully connected layer. Later the feature selection is performed with the help of an Enhanced Genetic Algorithm (EGA) that produces optimized solutions by implementing operations like mutations, crossover, and ensemble with Extreme Learning Machine (EGA-ELM) to classify the images as either melanoma or non-melanoma. The proposed model certainly achieved higher accuracy and effective performance. Finally, the obtained results are to be compared with other popular classifying algorithms like Support Vector Machine (SVM) and various other models.
KeywordsSkin Cancer Genetic Algorithm Extreme Learning Machine (ELM) CNN Optimization
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