Downloads: 2 | Views: 157 | Weekly Hits: ⮙2 | Monthly Hits: ⮙2
Research Paper | Computer Science and Information Technology | India | Volume 12 Issue 10, October 2023 | Popularity: 5.2 / 10
Modeling of Dragonfly Algorithm with Deep Learning for Skin Cancer Diagnosis on Dermoscopic Images
Vijay Arumugam R., Saravanan S.
Abstract: Skin cancer, a widespread and possibly life-threatening condition, requires an earlier and accurate diagnosis for efficient involvement. Dermoscopic images, providing a window into skin lesions, gives a useful resource for medical specialists in this context. This article goals to develop a complex architecture to detect skin cancer employing dermatoscopy images, integrating cutting-edge techniques in image analysis, machine learning, and artificial intelligence. This manuscript introduces the Dragonfly Algorithm with Deep Learning for Skin Cancer Diagnoses on Dermoscopy Images (DFADL-SCDDI) method. Our technique integrates advanced methods namely feature extraction, preprocessing, classification, and parameter optimization to increase the reliability and of accuracy identification. For image preprocessing, we exploit the Gabor filter (GF), a robust tool for enriching texture and structure data in images. Feature extraction has been executed employing a Capsule Network (CapsNet). CapsNet is a deep learning (DL) model that exceeds in capturing hierarchical and in-depth features in images. Classification is conducted by a Gated Recurrent Unit (GRU), a kind of recurrent neural network (RNN) ability to model sequential patterns and dependencies within the feature representations. To additional improve the model's effectiveness; we implement the Dragonfly Algorithm (DA) for parameter tuning. The DA has a powerful optimization system stimulated by nature, developed for enhancing hyperparameters efficiently, consequently higher the model's diagnostic accuracy. The proposed architecture is assessed on a large database of dermatoscopy images, signifying its effectiveness in skin cancer detection. The outcomes exhibit substantial enhancement in reliability and accuracy compared to traditional systems.
Keywords: Dragonfly Algorithm; Dermoscopy; Gated Recurrent Unit; Deep Learning; Parameter Tuning
Edition: Volume 12 Issue 10, October 2023
Pages: 1916 - 1922
DOI: https://www.doi.org/10.21275/SR231025120749
Make Sure to Disable the Pop-Up Blocker of Web Browser
Similar Articles
Downloads: 0
Survey Paper, Computer Science and Information Technology, China, Volume 10 Issue 12, December 2021
Pages: 299 - 304A Survey of Clustering Algorithms for Streaming
Denis Patrick Bell, Yang Chunting
Downloads: 0
Research Paper, Computer Science and Information Technology, Kenya, Volume 10 Issue 6, June 2021
Pages: 1621 - 1628Enterprise Resource Planning Integration and Performance of Safaricom Public Limited Company Kenya
Wambui Caroline, Tumuti Joshua
Downloads: 0
Case Studies, Computer Science and Information Technology, India, Volume 11 Issue 6, June 2022
Pages: 1356 - 1365The Life-Saving Mission for COVID-19 Vaccination on Google Cloud (GC) Ecosystem
Ramamurthy Valavandan, Kumaraswamy Reddy, Prasanth Parayatham, Ubaiyadulla Sherif, Pallav Kohli, Vikram Sharma, Pragathi S, Vijay R, Surasa Mukherjee, Nitin Ambekar, Dinesh Sai Teja Neeli, Santosh Baran, Vijender Singh, Saurabh Uniyal, Praveen B, Musheer Ahmed N
Downloads: 0
Review Papers, Computer Science and Information Technology, India, Volume 11 Issue 6, June 2022
Pages: 1784 - 1787Non-Fungible Tokens: The Future of Digital Collectibles and Assets
Harshal Jaywant Chavan
Downloads: 0
Review Papers, Computer Science and Information Technology, Qatar, Volume 11 Issue 12, December 2022
Pages: 189 - 197Quran Ontology: Review on Recent Research Issues
Rasha I. Ahmed, Mohamed H. Sayed, Talaat M. Wahbi