Fully‐automatic identification of gynaecological abnormality using a new adaptive frequency filter and histogram of oriented gradients ( HOG )-Reference-Cited by-同舟云学术

Fully‐automatic identification of gynaecological abnormality using a new adaptive frequency filter and histogram of oriented gradients ( HOG )

Published:2021-08-13 Issue: Volume: Page:
ISSN:0266-4720
Container-title:Expert Systems
language:en
Short-container-title:Expert Systems

Author:

Hussein Ihsan Jasim¹,Burhanuddin Mohd Aboobaider²,Mohammed Mazin Abed³^ORCID,Benameur Narjes⁴,Maashi Marwah Suliman⁵,Maashi Mashael S.⁶

Affiliation:

1. BIOCORE Research Group, Faculty of Information & Communication Technology Universiti Teknikal Malaysia Melaka Durian Tunggal Malaysia

2. Director of UTeM International Centre, BIOCORE Research Group, Faculty of Information & Communication Technology Universiti Teknikal Malaysia Melaka Durian Tunggal Malaysia

3. College of Computer Science and Information Technology University of Anbar Ramadi Iraq

4. Laboratory of Biophysics and Medical Technology Higher Institute of Medical Technologies of Tunis, University of Tunis El Manar Tunis Tunisia

5. Medical Laboratory Science Department, Faculty of Applied Medical Science King Abdulaziz University Jeddah Saudi Arabia

6. Software Engineering Department, College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/exsy.12789

Reference40 articles.

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5. Ultrasound-based tissue characterization and classification of fatty liver disease: A screening and diagnostic paradigm

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