Nazlıbilek, Sedat

Profile Picture
Profile URL
https://hdl.handle.net/20.500.14411/8361
Name Variants
S.,Nazlibilek
N., Sedat
Nazlıbilek,S.
Sedat, Nazlıbilek
N.,Sedat
Nazlibilek,S.
S., Nazlibilek
S.,Nazlıbilek
Sedat, Nazlibilek
Nazlıbilek, Sedat
Nazlibilek, Sedat
Job Title
Doçent Doktor
Email Address
Main Affiliation
Department of Mechatronics Engineering
Status
Former Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID

Sustainable Development Goals

5

GENDER EQUALITY
GENDER EQUALITY Logo

0

Research Products

14

LIFE BELOW WATER
LIFE BELOW WATER Logo

2

Research Products

10

REDUCED INEQUALITIES
REDUCED INEQUALITIES Logo

0

Research Products

3

GOOD HEALTH AND WELL-BEING
GOOD HEALTH AND WELL-BEING Logo

1

Research Products

2

ZERO HUNGER
ZERO HUNGER Logo

0

Research Products

9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
INDUSTRY, INNOVATION AND INFRASTRUCTURE Logo

0

Research Products

16

PEACE, JUSTICE AND STRONG INSTITUTIONS
PEACE, JUSTICE AND STRONG INSTITUTIONS Logo

0

Research Products

11

SUSTAINABLE CITIES AND COMMUNITIES
SUSTAINABLE CITIES AND COMMUNITIES Logo

1

Research Products

8

DECENT WORK AND ECONOMIC GROWTH
DECENT WORK AND ECONOMIC GROWTH Logo

0

Research Products

13

CLIMATE ACTION
CLIMATE ACTION Logo

0

Research Products

4

QUALITY EDUCATION
QUALITY EDUCATION Logo

0

Research Products

6

CLEAN WATER AND SANITATION
CLEAN WATER AND SANITATION Logo

0

Research Products

1

NO POVERTY
NO POVERTY Logo

0

Research Products

15

LIFE ON LAND
LIFE ON LAND Logo

0

Research Products

17

PARTNERSHIPS FOR THE GOALS
PARTNERSHIPS FOR THE GOALS Logo

1

Research Products

7

AFFORDABLE AND CLEAN ENERGY
AFFORDABLE AND CLEAN ENERGY Logo

1

Research Products

12

RESPONSIBLE CONSUMPTION AND PRODUCTION
RESPONSIBLE CONSUMPTION AND PRODUCTION Logo

0

Research Products
This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.
Scholarly Output

22

Articles

14

Views / Downloads

5/0

Supervised MSc Theses

3

Supervised PhD Theses

3

WoS Citation Count

245

Scopus Citation Count

302

WoS h-index

7

Scopus h-index

8

Patents

0

Projects

0

WoS Citations per Publication

11.14

Scopus Citations per Publication

13.73

Open Access Source

1

Supervised Theses

6

Google Analytics Visitor Traffic

JournalCount
Measurement7
Indian Journal of Pure and Applied Physics2
IEEE Transactions on Instrumentation and Measurement2
20th Annual International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2013 -- 20th Annual International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2013 -- 20 September 2013 through 20 September 2013 -- Ankara -- 1022761
International Conference of Control, Dynamic Systems, and Robotics -- 4th International Conference of Control, Dynamic Systems, and Robotics, CDSR 2017 -- 21 August 2017 through 23 August 2017 -- Toronto -- 1399181
Current Page: 1 / 2

Scopus Quartile Distribution

Competency Cloud

GCRIS Competency Cloud

Filters

20151
Reset filters

Settings

Author: Kakilli, AdnanSubject: Binary robust invariant scalable keypoint (BRISK)

Scholarly Output Search Results

Now showing 1 - 1 of 1
  • Thumbnail Image
    Article
    Citation - WoS: 5
    Citation - Scopus: 5
    A Study on the Performance of Magnetic Material Identification System by Sift-Brisk and Neural Network Methods
    (Ieee-inst Electrical Electronics Engineers inc, 2015) Ege, Yavuz; Nazlibilek, Sedat; Kakilli, Adnan; Citak, Hakan; Kalender, Osman; Karacor, Deniz; Sengul, Gokhan
    Industry requires low-cost, low-power consumption, and autonomous remote sensing systems for detecting and identifying magnetic materials. Magnetic anomaly detection is one of the methods that meet these requirements. This paper aims to detect and identify magnetic materials by the use of magnetic anomalies of the Earth's magnetic field created by some buried materials. A new measurement system that can determine the images of the upper surfaces of buried magnetic materials is developed. The system consists of a platform whose position is automatically controlled in x-axis and y-axis and a KMZ51 anisotropic magneto-resistive sensor assembly with 24 sensors mounted on the platform. A new identification system based on scale-invariant feature transform (SIFT)-binary robust invariant scalable keypoints (BRISKs) as keypoint and descriptor, respectively, is developed for identification by matching the similar images of magnetic anomalies. The results are compared by the conventional principal component analysis and neural net algorithms. On the six selected samples and the combinations of these samples, 100% correct classification rates were obtained.