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$25 USD / hora
Bandera de TURKEY
ankara, turkey
$25 USD / hora
Aquí son las 1:33 p. m.
Se unió el junio 5, 2017
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Engin F.

@enginfirat

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$25 USD / hora
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ankara, turkey
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Computer Engineer

I have been working as a Software Engineer for about ~6 years. Since graduation I mainly work on projects that are developed by using C, C++ and Java that work on ARM and entrance level Intel processors like Atom processors. I am interested in Computer Vision and Machine Learning and I mostly participated in projects that are related with these disciplines such as, object detection/recognition/tracking. I worked on development of algorithms that run on DSPs and GPUs in which efficiency and performance is main consideration.

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Educación

Physics, BSc. 2.97

Orta Dogu Teknik Üniversitesi, Turkey 2006 - 2012
(6 años)

Computer Engineering, BSc. 2.8

Orta Dogu Teknik Üniversitesi, Turkey 2006 - 2012
(6 años)

Calificaciones

Improving Deep Nural Networks, Hyperparameter tuning, Regularization and Optimization

deeplearning.ai
2017
Coursera, https://www.coursera.org/account/accomplishments/verify/DA8C2MBJ3587

Neural Networks and Deep Learning

deeplearning.ai
2017
Coursera, https://www.coursera.org/account/accomplishments/verify/X772BJP5M56P

Machine Learning Foundations: A Case Study Approach

University of Washington
2016
Coursera, https://www.coursera.org/account/accomplishments/verify/8SDYSYFL2ZD6

Publicaciones

Modelling, Simulation and Visualization of Vehicle Dynamics

USMOS2011, http://usmos.metu.edu.tr/
In this paper, a software which is aimed for physical modeling, simulation and visualization of a vehicle is presented. A physical modeling of a vehicle consists of modeling all the components of a vehicle which affects vehicle dynamics. Hence components called engine, clutch, gear-box, differential is modeled in the system. Moreover, tire and wheel models, steering wheel box models, brake models and aerodynamic models of vehicle are implemented in the system.

Multi-view Face Detection with One Classifier for Video Analytics Systems

VAAM 2014, ICPR2014, Springer
In a video analytics for audience measurement system, dwell time, gaze, and opportunity-to-see statistics are required most of the time. To generate these statistics, more than one face detector is used in order to capture both profile and frontal faces. In this paper, we present a novel approach for face detection in video analytics. The assumption is that; the face occurrences are limited in such systems and one classifier is able to capture all of these occurrences.

Comparison of Facial Alignment Techniques with Test Results on Gender Detection Task

VAAM 2014, ICPR2014, Springer
In this paper, different facial alignment techniques are revised in terms of their effects on machine learning algorithms. There is no special reason on selecting gender classification task, any other task could have been chosen. In audience measurement systems, many important demographics, i.e. gender, age, facial expression, can be measured by using machine learning algorithms. Any performance enhancement on any machine learning algorithm becomes important.

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