Classification of Lung Nodule Using Hybridized Deep Feature Technique
Deep learning techniques have become very popular among Artificial Intelligence (AI) techniques in many areas of life. Among many types of deep learning techniques, Convolutional Neural Networks (CNN) can be useful in image classification applications. In this work, a hybridized approach has been fo...
Main Authors: | Malin Bruntha, Immanuel Alex Pandian, Siril Sam Abraham |
---|---|
Format: | Article |
Language: | fas |
Published: |
University of Tehran
2020-12-01
|
Series: | Journal of Information Technology Management |
Subjects: | |
Online Access: | https://jitm.ut.ac.ir/article_79369_c5abf1274531aa0c9c8485bc78aee6ae.pdf |
Similar Items
-
A novel hybridized feature extraction approach for lung nodule classification based on transfer learning technique
by: P Malin Bruntha, et al.
Published: (2022-01-01) -
Comparative Study of Herbal Leaves Classification using Hybrid of GLCM-SVM and GLCM-CNN
by: Purnawansyah Purnawansyah, et al.
Published: (2023-08-01) -
GF-2 Data for Lithological Classification Using Texture Features and PCA/ICA Methods in Jixi, Heilongjiang, China
by: Tianyi Chen, et al.
Published: (2023-09-01) -
Deep and Hybrid Learning Technique for Early Detection of Tuberculosis Based on X-ray Images Using Feature Fusion
by: Suliman Mohamed Fati, et al.
Published: (2022-07-01) -
Three combination value of extraction features on GLCM for detecting pothole and asphalt road
by: Yoke Kusuma Arbawa, et al.
Published: (2021-01-01)