Deep Learning for the Detection of Acute Lymphoblastic Leukemia Subtypes on Microscopic Images: A Systematic Literature Review-Reference-Cited by-同舟云学术

Deep Learning for the Detection of Acute Lymphoblastic Leukemia Subtypes on Microscopic Images: A Systematic Literature Review

Published:2023 Issue: Volume:11 Page:16108-16127
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Mustaqim Tanzilal¹^ORCID,Fatichah Chastine¹^ORCID,Suciati Nanik¹^ORCID

Affiliation:

1. Department of Informatics, Faculty of Intelligent Electrical and Informatics Technology, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia

Funder

Kementerian Pendidikan dan Kebudayaan

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/ielx7/6287639/10005208/10044672.pdf?arnumber=10044672

Reference116 articles.

1. A Review of Object Detection Models Based on Convolutional Neural Network

2. Overview of two-stage object detection algorithms

3. End-to-end object detection with transformers;carion;Proc Eur Conf Comput Vis,2020

4. An image is worth 16×16 words: Transformers for image recognition at scale;dosovitskiy;arXiv 2010 11929,2020

5. Classification of acute lymphoblastic leukemia on white blood cell microscopy images based on instance segmentation using mask R-CNN;revanda;Int J Intell Eng Syst,2022

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3. Detection and Sub-Classification of Acute Lymphoblastic Leukemia Cell Types from the Microscopic Images Based on The Object Detection Model YOLOV5;2024 14th International Conference on Electrical Engineering (ICEENG);2024-05-21

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