Impact of fine-tuning parameters of convolutional neural network for skin cancer detection
Abstract Melanoma skin cancer is a deadly disease with a high mortality rate. A prompt diagnosis can aid in the treatment of the disease and potentially save the patient’s life. Artificial intelligence methods can help diagnose cancer at a rapid speed. The literature has employed numerous Machine Le...
Saved in:
| Main Authors: | Zaib Unnisa, Asadullah Tariq, Nadeem Sarwar, Irfanud Din, Mohamed Adel Serhani, Zouheir Trabelsi |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-99529-0 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Automatic melanoma and non-melanoma skin cancer diagnosis using advanced adaptive fine-tuned convolution neural networks
by: Muhammad Amir Khan, et al.
Published: (2025-04-01) -
Comparative Study: Flower Classification using Deep Learning, SMOTE and Fine-Tuning
by: Vincentius Praskatama, et al.
Published: (2024-11-01) -
A Classifier Model Using Fine-Tuned Convolutional Neural Network and Transfer Learning Approaches for Prostate Cancer Detection
by: Murat Sarıateş, et al.
Published: (2024-12-01) -
A fine tuned EfficientNet-B0 convolutional neural network for accurate and efficient classification of apple leaf diseases
by: Hassan Ali, et al.
Published: (2025-07-01) -
Enhancing Skin Disease Diagnosis Through Fine-Tune Convolutional Neural Network: A Comparative Study with Multi-class Approach
by: Najnin Akter Ringky, et al.
Published: (2023-09-01)