Khan, Muhammad Umer

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Profile URL
https://hdl.handle.net/20.500.14411/6656
Name Variants
Khan, Muhammad Umer
K.,Muhammad Umer
Muhammad Umer, Khan
Khan,Muhammad Umer
M.U.Khan
M., Khan
M.,Khan
Khan U.
Khan M.
Khan,M.U.
M. U. Khan
Umer Khan M.
K., Muhammad Umer
Muhammad Umer Khan
Khan, Umer
Khan, Muhammed Umer
Khan, M. U.
Khan, M.U
Job Title
Yardımcı Doçent
Email Address
umer.khan@atilim.edu.tr
Main Affiliation
Mechatronics Engineering
Status
Website
ORCID ID
0000-0002-9195-3477
Scopus Author ID
57209876827
Turkish CoHE Profile ID
277006
Google Scholar ID
8h-JrH8AAAAJ
WoS Researcher ID
N-5478-2016

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2

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4

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11

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0

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14

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0

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6

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0

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1

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0

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5

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0

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9

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1

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16

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0

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17

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1

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15

LIFE ON LAND
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0

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10

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0

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7

AFFORDABLE AND CLEAN ENERGY
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4

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8

DECENT WORK AND ECONOMIC GROWTH
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0

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4

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12

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3

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13

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Documents

37

Citations

625

h-index

13

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Documents

30

Citations

463

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Scholarly Output

36

Articles

14

Views / Downloads

178/1580

Supervised MSc Theses

10

Supervised PhD Theses

0

WoS Citation Count

240

Scopus Citation Count

358

WoS h-index

7

Scopus h-index

8

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0

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0

WoS Citations per Publication

6.67

Scopus Citations per Publication

9.94

Open Access Source

10

Supervised Theses

10

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JournalCount
2018 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, MESA 2018 -- 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, MESA 2018 -- 2 July 2018 through 4 July 2018 -- Oulu -- 1391112
Applied Sciences2
2019 2nd International Conference on Communication, Computing and Digital Systems, C-CODE 2019 -- 2nd International Conference on Communication, Computing and Digital Systems, C-CODE 2019 -- 6 March 2019 through 7 March 2019 -- Islamabad -- 1469971
2020 7th International Conference on Electrical and Electronics Engineering, ICEEE 2020 -- 7th International Conference on Electrical and Electronics Engineering, ICEEE 2020 -- 14 April 2020 through 16 April 2020 -- Antalya -- 1604501
2021 IEEE International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2021 -- 2021 IEEE International Conference on Robotics, Automation and Artificial Intelligence, RAAI 2021 -- 21 April 2021 through 23 April 2021 -- Virtual, Online -- 1767941
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    Review
    Citation - WoS: 18
    Citation - Scopus: 30
    Review of Modern Forest Fire Detection Techniques: Innovations in Image Processing and Deep Learning
    (Mdpi, 2024) Ozel, Berk; Alam, Muhammad Shahab; Khan, Muhammad Umer
    Fire detection and extinguishing systems are critical for safeguarding lives and minimizing property damage. These systems are especially vital in combating forest fires. In recent years, several forest fires have set records for their size, duration, and level of destruction. Traditional fire detection methods, such as smoke and heat sensors, have limitations, prompting the development of innovative approaches using advanced technologies. Utilizing image processing, computer vision, and deep learning algorithms, we can now detect fires with exceptional accuracy and respond promptly to mitigate their impact. In this article, we conduct a comprehensive review of articles from 2013 to 2023, exploring how these technologies are applied in fire detection and extinguishing. We delve into modern techniques enabling real-time analysis of the visual data captured by cameras or satellites, facilitating the detection of smoke, flames, and other fire-related cues. Furthermore, we explore the utilization of deep learning and machine learning in training intelligent algorithms to recognize fire patterns and features. Through a comprehensive examination of current research and development, this review aims to provide insights into the potential and future directions of fire detection and extinguishing using image processing, computer vision, and deep learning.