Skip to main navigation
Skip to search
Skip to main content

King Fahd University of Petroleum & Minerals Home

Help & FAQ

Home
Profiles
Research units
Projects
Research output
Prizes
Student theses

Search by expertise, name or affiliation

MOVING PART IMAGE PARTITIONING FOR WALKING GAIT IDENTIFICATION

Elsayed Elalfy (Inventor)

King Fahd University of Petroleum & Minerals
Interdisciplinary Research Center for Intelligent Secure Systems
Department of Information and Computer Science

Research output: Patent

Overview

Original language	English
Patent number	US10115006
State	Published - 2018

Cite this

APA
Author
BIBTEX
Harvard
Standard
RIS
Vancouver

Elalfy, E. (2018). MOVING PART IMAGE PARTITIONING FOR WALKING GAIT IDENTIFICATION. (Patent No. US10115006).

Elalfy, Elsayed (Inventor). / MOVING PART IMAGE PARTITIONING FOR WALKING GAIT IDENTIFICATION. Patent No.: US10115006.

@misc{3f85bd190c0b406ab964ace2a62409ce,

title = "MOVING PART IMAGE PARTITIONING FOR WALKING GAIT IDENTIFICATION",

author = "Elsayed Elalfy",

year = "2018",

language = "English",

type = "Patent",

note = "US10115006",

}

Elalfy, E, MOVING PART IMAGE PARTITIONING FOR WALKING GAIT IDENTIFICATION, Patent No. US10115006.

MOVING PART IMAGE PARTITIONING FOR WALKING GAIT IDENTIFICATION. / Elalfy, Elsayed (Inventor).
Patent No.: US10115006.

Research output: Patent

TY - PAT

T1 - MOVING PART IMAGE PARTITIONING FOR WALKING GAIT IDENTIFICATION

AU - Elalfy, Elsayed

PY - 2018

Y1 - 2018

M3 - Patent

M1 - US10115006

ER -

Elalfy E, inventor. MOVING PART IMAGE PARTITIONING FOR WALKING GAIT IDENTIFICATION. US10115006. 2018.

Powered by Pure, Scopus & Elsevier Fingerprint Engine™

All content on this site: Copyright © 2025 King Fahd University of Petroleum & Minerals, its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply

We use cookies to help provide and enhance our service and tailor content. By continuing you agree to the use of cookies

About web accessibility

Report vulnerability