0% Complete
Home
/
14th International Conference on Computer and Knowledge Engineering
Enhanced Skin Cancer Classification Using Deep Learning and Gradient Boosting Techniques
Authors :
Amir Mohammad Sharafaddini
1
Najme Mansouri
2
1- Shahid Bahonar University of Kerman
2- Shahid Bahonar University of Kerman
Keywords :
Skin cancer classification،machine learning،deep learning،CatBoost،Principal Component Analysis
Abstract :
Skin cancer is a common and potentially fatal disease that requires early and accurate diagnosis for effective treatment. This paper presents a machine learning-based approach for classifying skin cancer using dermoscopic images from the HAM10000 dataset. We utilize pre-trained models, specifically ResNet-50 and DenseNet-201, for feature extraction, followed by dimensionality reduction using Principal Component Analysis (PCA). The resulting feature set is then classified using CatBoost, a state-of-the-art gradient boosting algorithm. The proposed model achieved an impressive accuracy of 98.15% and a log loss of 0.2141. We compare our results with nine recent studies and demonstrate the superior performance of the proposed approach. This study highlights the potential of integrating advanced deep learning techniques and boosting algorithms to enhance the accuracy and reliability of automated skin cancer diagnosis systems.
Papers List
List of archived papers
Bipartite link prediction improvement using the effective utilization of edge betweenness centrality
Sadegh Sulaimany Sulaimany - Yasin Amini
Optimizing MR Image Registration for Accurate Brain Volume Measurement in Children with Autism Spectrum Disorder
Shiva Sanati - Mahdi Saadatmand
MCRS-SAE : multi criteria recommender system based on sparse autoencoder
Amir reza Kalantarnezhad - Javad Hamidzadeh
EfficientNetB0’s Hybrid Approach for Brain Tumor Classification from MRI Images Using Deep Learning and Bagging Trees
Yeganeh Modaresnia - Farhad Abedinzadeh Torghabeh - Seyyed Abed Hosseini
An optimal workflow scheduling method in cloud-fog computing using three-objective Harris-Hawks algorithm
Ahmadreza Montazerolghaem - Maryam Khosravi - Fatemeh Rezaee
Blind image quality assessment based on Multi-resolution Local Structures
Seyed Majid Khorashadizadeh - Mehdi Sadeghi Bakhi - Fatemeh Seifishahpar - AliMohammad Latif
UAV-based Firefighting by Multi-agent Reinforcement Learning
Reza Shami Tanha - Mohsen Hooshmand - Mohsen Afsharchi
Using Deep Learning for Classification of Lung Cancer on CT Images in Ardabil Province
Mohammad Ali Javadzadeh Barzaki - Jafar Abdollahi - Mohammad Negaresh - Maryam Salimi - Hadi Zolfeghari - Mohsen Mohammadi - Asma Salmani - Rona Jannati - Firouz Amani
An effective hybrid algorithm for locating splicing forgery image
Seyed Hesamoddin Hosseini - Amene Vatanparast - Amir Hossein Taherinia
IR-LPR: Large Scale of Iranian License Plate Recognition Dataset
Mahdi Rahmani - Melika Sabaghian - Seyyedeh Mahila Moghadami - Mohammad Mohsen Talaie - Mahdi Naghibi - Mohammad Ali Keyvanrad
more
Samin Hamayesh - Version 42.2.1