Integration of Deep Learning Architectures With GRU for Automated Leukemia Detection in Peripheral Blood Smear Images

Integration of Deep Learning Architectures With GRU for Automated Leukemia Detection in Peripheral Blood Smear Images

This paper investigates the integration of deep learning (DL) architectures with Recurrent Neural Networks (RNNs) for automated leukemia detection in Peripheral Blood Smear (PBS) images. Models such as DenseNet201, EfficientNetB3, Inception v3, InceptionResNetV2, MobileNetV2, ResNet50, VGG16, and Xc...

Full description

Saved in:
Bibliographic Details
Main Authors: Amit Kumar Bairwa, Anita Shrotriya, Priyanka Mathur, Sandeep Joshi, Sakshi Shringi, Ambika Kumari
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Leukemia detection (LD)
peripheral blood smear (PBS) images
gated recurrent unit (GRU)
medical image analysis
Online Access:https://ieeexplore.ieee.org/document/10979923/
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://ieeexplore.ieee.org/document/10979923/

Similar Items