Güneş, Ahmet

Profile Picture
Profile URL
https://hdl.handle.net/20.500.14411/7663
Name Variants
A.,Gunes
Gunes, Ahmet
G., Ahmet
A., Gunes
Ahmet, Gunes
G.,Ahmet
Gunes,A.
Güneş, Ahmet
Güneş,A.
A.,Güneş
Ahmet, Güneş
Job Title
Doktor Öğretim Üyesi
Email Address
ahmet.gunes@atilim.edu.tr
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

NO POVERTY1
NO POVERTY
0
Research Products
ZERO HUNGER2
ZERO HUNGER
1
Research Products
GOOD HEALTH AND WELL-BEING3
GOOD HEALTH AND WELL-BEING
0
Research Products
QUALITY EDUCATION4
QUALITY EDUCATION
0
Research Products
GENDER EQUALITY5
GENDER EQUALITY
0
Research Products
CLEAN WATER AND SANITATION6
CLEAN WATER AND SANITATION
0
Research Products
AFFORDABLE AND CLEAN ENERGY7
AFFORDABLE AND CLEAN ENERGY
0
Research Products
DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
0
Research Products
REDUCED INEQUALITIES10
REDUCED INEQUALITIES
0
Research Products
SUSTAINABLE CITIES AND COMMUNITIES11
SUSTAINABLE CITIES AND COMMUNITIES
0
Research Products
RESPONSIBLE CONSUMPTION AND PRODUCTION12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
CLIMATE ACTION13
CLIMATE ACTION
0
Research Products
LIFE BELOW WATER14
LIFE BELOW WATER
0
Research Products
LIFE ON LAND15
LIFE ON LAND
0
Research Products
PEACE, JUSTICE AND STRONG INSTITUTIONS16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
0
Research Products
This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.
Scholarly Output

12

Articles

3

Views / Downloads

0/0

Supervised MSc Theses

0

Supervised PhD Theses

1

WoS Citation Count

42

Scopus Citation Count

55

Patents

0

Projects

0

WoS Citations per Publication

3.50

Scopus Citations per Publication

4.58

Open Access Source

2

Supervised Theses

1

JournalCount
Applied Sciences2
26th IEEE Signal Processing and Communications Applications Conference (SIU) -- MAY 02-05, 2018 -- Izmir, TURKEY2
26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 -- 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 -- 2 May 2018 through 5 May 2018 -- Izmir -- 1377802
IEEE Microwave and Wireless Components Letters1
International Geoscience and Remote Sensing Symposium (IGARSS) -- 39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 -- 28 July 2019 through 2 August 2019 -- Yokohama -- 1547921
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Type: Conference Object

Scholarly Output Search Results

Now showing 1 - 8 of 8
  • Thumbnail Image
    Conference Object
    Multiple Underwater Target Bearing Tracking Using Member Filter
    (Ieee, 2018) Gunes, Ahmet; Guldogan, Mehmet B.
    Underwater acoustic vector sensors (AVS) are devices which can measure scalar pressure and three dimensional acceleration or particle velocity with only one sensor. By using these four measurements, target detection and tracking is possible. In case multiple targets exist, multi-target detection and tracking methods must be applied. Because these methods are more general, the algorithms are more involved and complex. In this framework, multi-target multi-Bernoulli (MeMBer) is a promising filter based on random finite sets (RFS) for multi-target tracking problems. In this work, for the first time in the literature, MeMBer filter is analyzed using a single underwater acoustic vector sensor in a scenario including two targets. Simulation results indicate that MeMBer filter can successfully track the targets.
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 1
    Comparison of Target Detection Performance for Radiance and Reflectance Domain in Vnir Hyperspectral Images
    (Institute of Electrical and Electronics Engineers Inc., 2019) Ozdil,O.; Gunes,A.; Esin,Y.E.; Demirel,B.; Ozturk,S.
    In this paper, the hyperspectral detection of targets in visible-near infrared (VNIR) images is studied. The change of radiance domain signatures in images taken in different locations, time and altitudes are analyzed. A new radiance domain detection scheme for VNIR images under 1000 m altitude is proposed. The analysis shows that the radiance domain signatures of each target, that are collected from an image taken at 10 m altitude, can be effectively used for pure pixel target detection in other VNIR images taken at altitudes between 10 - 1000 m. The proposed approach is tested using several target types and on images taken at different altitudes and environmental conditions. Our results show that target detection in radiance domain provides a cheaper, easier and effective alternative to reflectance domain, in VNIR images. © 2019 IEEE.
  • Thumbnail Image
    Conference Object
    Shape Recognition With Low Cost Sensors
    (Ieee, 2018) Saloglu, Keziban; Hosafci, Arda; Birbilen, Merve; Bulut, Yigit A.; Gunes, Ahmet
    This paper proposes a method to recognize the shape of some objects that have different geometrical properties using an infra-red sensor.To that end, a mechanism that has two degrees of freedom is designed. Scanning of the different objects are obtained. Noise on scanning output is removed. Finally, all the outputs for different objects are discussed to obtain the specifications to do shape recognition.
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 1
    Multiple Underwater Target Bearing Tracking Using Member Filter;
    (Institute of Electrical and Electronics Engineers Inc., 2018) Gunes,A.; Guldogan,M.B.
    Underwater acoustic vector sensors (AVS) are devices which can measure scalar pressure and three dimensional acceleration or particle velocity with only one sensor. By using these four measurements, target detection and tracking is possible. In case multiple targets exist, multi-target detection and tracking methods must be applied. Because these methods are more general, the algorithms are more involved and complex. In this framework, multi-target multi-Bernoulli (MeMBer) is a promising filter based on random finite sets (RFS) for multi-target tracking problems. In this work, for the first time in the literature, MeMBer filter is analyzed using a single underwater acoustic vector sensor in a scenario including two targets. Simulation results indicate that MeMBer filter can successfully track the targets. © 2018 IEEE.
  • Thumbnail Image
    Conference Object
    Shape Recognition With Low Cost Sensors;
    (Institute of Electrical and Electronics Engineers Inc., 2018) Saloglu,K.; Hosafci,A.; Birbilen,M.; Bulut,Y.A.; Gunes,A.
    This paper proposes a method to recognize the shape of some objects that have different geometrical properties using an infra-red sensor. To that end, a mechanism that has two degrees of freedom is designed. Scanning of the different objects are obtained. Noise on scanning output is removed. Finally, all the outputs for different objects are discussed to obtain the specifications to do shape recognition. © 2018 IEEE.
  • Thumbnail Image
    Conference Object
    Citation - WoS: 3
    Comparison of Target Detection Performance for Radiance and Reflectance Domain in Vnir Hyperspectral Images
    (Ieee, 2019) Ozdil, Omer; Gunes, Ahmet; Esin, Yunus Emre; Demirel, Berkan; Ozturk, Safak
    In this paper, the hyperspectral detection of targets in visible-near infrared (VNIR) images is studied. The change of radiance domain signatures in images taken in different locations, time and altitudes are analyzed. A new radiance domain detection scheme for VNIR images under 1000 m altitude is proposed. The analysis shows that the radiance domain signatures of each target, that are collected from an image taken at 10 m altitude, can be effectively used for pure pixel target detection in other VNIR images taken at altitudes between 10 - 1000 m. The proposed approach is tested using several target types and on images taken at different altitudes and environmental conditions. Our results show that target detection in radiance domain provides a cheaper, easier and effective alternative to reflectance domain, in VNIR images.
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 2
    4-Stage Target Detection Approach in Hyperspectral Images
    (IEEE Computer Society, 2018) Ozdil,O.; Gunes,A.; Esin,Y.E.; Ozturk,S.; Demirel,B.
    Practical target detection systems require an automatic way to detect targets with high accuracy. Detection errors is not tolerable and they should be reduced as much as possible. In classical detection systems, generally single target detection algorithm is performed and the result will be evaluated according to the thresholding techniques. However, in these uncontrolled systems, false alarm rate strongly depends on the thresholding technique success. It is very hard to find a general and constant threshold value for images taken at different conditions and practical detection systems needs reliable threshold value. In this paper, we propose a new multi-stage target detection system which is the combination of different detection algorithms and thresholding technique. This system compose of 4-stages, i.e. namely 1-initial target detection (ACE, GLRT), 2-adaptive Constant False Alarm Rate (CFAR) thresholding, 3-spatially grouping, 4-statistical confidence operation. This system configuration removes the need for interactive user and it automatically implements confirmation and rejection steps. Moreover, this system can be used both for pure pixel and subpixel target detection purposes and it reduces computational processing time considerably with the implementation of consequtive processing stages. © 2018 IEEE.
  • Thumbnail Image
    Conference Object
    4-stage< Target Detection Approach in Hyperspectral Images
    (Ieee, 2018) Ozdil, Omer; Gunes, Ahmet; Esin, Yunus Emre; Ozturk, Safak; Demirel, Berkan
    Practical target detection systems require an automatic way to detect targets with high accuracy. Detection errors is not tolerable and they should be reduced as much as possible. In classical detection systems, generally single target detection algorithm is performed and the result will be evaluated according to the thresholding techniques. However, in these uncontrolled systems, false alarm rate strongly depends on the thresholding technique success. It is very hard to find a general and constant threshold value for images taken at different conditions and practical detection systems needs reliable threshold value. In this paper, we propose a new multi-stage target detection system which is the combination of different detection algorithms and thresholding technique. This system compose of 4-stages, i.e. namely 1-initial target detection (ACE, GLRT), 2-adaptive Constant False Alarm Rate (CFAR) thresholding, 3-spatially grouping, 4-statistical confidence operation. This system configuration removes the need for interactive user and it automatically implements confirmation and rejection steps. Moreover, this system can be used both for pure pixel and subpixel target detection purposes and it reduces computational processing time considerably with the implementation of consequtive processing stages.