Lightweight EfficientNetB3 Model Based on Depthwise Separable Convolutions for Enhancing Classification of Leukemia White Blood Cell Images-Reference-Cited by-同舟云学术

Lightweight EfficientNetB3 Model Based on Depthwise Separable Convolutions for Enhancing Classification of Leukemia White Blood Cell Images

Published:2023 Issue: Volume:11 Page:37203-37215
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Batool Amreen¹^ORCID,Byun Yung-Cheol²^ORCID

Affiliation:

1. Department of Electronic Engineering, Institute of Information Science and Technology, Jeju National University, Jeju, South Korea

2. Department of Computer Engineering, Institute of Information Science and Technology, Jeju National University, Jeju, South Korea

Funder

Ministry of Small and Medium-Sized Enterprises (SMEs) and Startups (MSS), South Korea, under the Regional Specialized Industry Development Plus Program

Korea Technology and Information Promotion Agency for SMEs

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10100945.pdf?arnumber=10100945

Reference66 articles.

1. A deep network designed for segmentation and classification of leukemia using fusion of the transfer learning models

2. A Deep Learning-Based Approach for the Diagnosis of Acute Lymphoblastic Leukemia

3. Convolutional Bi-LSTM Based Human Gait Recognition Using Video Sequences

4. BO-ALLCNN: Bayesian-Based Optimized CNN for Acute Lymphoblastic Leukemia Detection in Microscopic Blood Smear Images

5. Classification of white blood cells based on surf feature;noor;Suranaree J Sci Technol,2021

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