Evaluating CNN Architectures and Hyperparameter Tuning for Enhanced Lung Cancer Detection Using Transfer Learning

Evaluating CNN Architectures and Hyperparameter Tuning for Enhanced Lung Cancer Detection Using Transfer Learning

Accurate lung cancer detection is vital for timely diagnosis and treatment. This study evaluates the performance of six convolutional neural network (CNN) architectures, ResNet-50, VGG-16, ResNet-101, VGG-19, DenseNet-201, and EfficientNet-B4, using the LIDC-IDRI dataset. Models were assessed both i...

Full description

Saved in:
Bibliographic Details
Main Authors: Mohd Munazzer Ansari, Shailendra Kumar, Umair Tariq, Md Belal Bin Heyat, Faijan Akhtar, Mohd Ammar Bin Hayat, Eram Sayeed, Saba Parveen, Dustin Pomary
Format: Article
Language:English
Published: Wiley 2024-01-01
Series:Journal of Electrical and Computer Engineering
Online Access:http://dx.doi.org/10.1155/2024/3790617
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

http://dx.doi.org/10.1155/2024/3790617

Similar Items