Attention Enhanced InceptionNeXt-Based Hybrid Deep Learning Model for Lung Cancer Detection
Lung cancer is the most common cause of cancer-related mortality globally. Early diagnosis of this highly fatal and prevalent disease can significantly improve survival rates and prevent its progression. Computed tomography (CT) is the gold standard imaging modality for lung cancer diagnosis, offeri...
Saved in:
| Main Authors: | Burhanettin Ozdemir, Emrah Aslan, Ishak Pacal |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10872981/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
InceptMan: An InceptionNeXt-Based Architecture for End-to-End Mandible Reconstruction
by: Nattapon Kamboonsri, et al.
Published: (2025-01-01) -
ViSwNeXtNet Deep Patch-Wise Ensemble of Vision Transformers and ConvNeXt for Robust Binary Histopathology Classification
by: Özgen Arslan Solmaz, et al.
Published: (2025-06-01) -
A New Hybrid ConvViT Model for Dangerous Farm Insect Detection
by: Anil Utku, et al.
Published: (2025-02-01) -
An innovative deep learning framework for skin cancer detection employing ConvNeXtV2 and focal self-attention mechanisms
by: Burhanettin Ozdemir, et al.
Published: (2025-03-01) -
Enhancing Melanoma Diagnosis with Advanced Deep Learning Models Focusing on Vision Transformer, Swin Transformer, and ConvNeXt
by: Serra Aksoy, et al.
Published: (2024-08-01)