Personal details

Ahmet Ö. - Remote

Ahmet Ö.

Timezone: Istanbul (UTC+3)

Summary

• • • • • I have received the "Google Inside Look 2019 Award" from the Google. • • • • •

I have professional expertise in Computer Vision, Deep Learning, Machine Learning, Image Processing and Object Oriented Design! And, I have a master degree from Computer Vision field!

PLEASE SEE MY GITHUB TO CHECK MY SKILLS! : https://github.com/ahmetozlu

My papers about Computer Vision & Deep Learning:

YouTube: https://www.youtube.com/c/AhmetÖZLÜ/videos
Medium: https://ahmetozlu.medium.com/

→ Interest Areas: Computer Vision, Machine Learning, Deep Learning and Image Processing.

→ Technologies: TensorFlow, Keras API, dlib, OpenCV, scikit-learn, scikit-image, NumPy, SciPy, Pandas, python, OpenFace, OpenPose, Tesseract, RESTful API, Flask, Android, Gradle, Linux.

→ Case works: Face Recognition&Verification, Object Detection/Tracking/Counting, Image Analysis, Video Analysis, Designing&Training of CNNs, Feature Extractions and so on..

Work Experience

Senior software engineer
Garanti BBVA Technology | Feb 2018 - Present
Java
JBoss
Jenkins
Spring Boot
Swagger
RESTful API
- Design, lead development and maintenance of Online & Bulk SMS System of Garanti Bank (BBVA) which serves millions of users every day, and work on AI based research projects that have critical revenue impact. - Using Maven as dependency management tool, git for version control, Jenkins for Continuous Integration and JBoss as deployment tool.
Computer Vision Researcher
SiMiT Lab | Jul 2017 - Present
Python
Linux
OpenCV
Ubuntu
NumPy
Matplotlib
Pandas
TensorFlow
Keras
- Researching novel facial image processing and analysis, under the supervision of Prof. Hazim Kemal Ekenel. - Developing multi-view face recognition system by my own design CNN architecture to improve accuracy and speed of current face recognition systems.

Personal Projects

TensorFlow Object Detection APIIconOpenNewWindows
2018
Python
NumPy
Machine Learning
Computer Vision
Deep Learning
TensorFlow
The TensorFlow Object Counting API is an open source framework built on top of TensorFlow that makes it easy to develop object counting systems!
Collaborative City Co-design PlatfOrm (CP3O)IconOpenNewWindows
2017
AI (artificial intelligence)
C3PO aims at providing a Cloud collaborative and semantic platform for city co-design. The C3PO platform is unique in that it covers the whole urban project development process where cities empower, encourage and guide different stakeholders to develop an urban project together. C3PO does not intend to replace or modify the existing applications offering unique but partial solutions of city co-design but can be seen as an open and generic intermediary that enables the interaction between existing applications through a unique multi-dimensional semantic repository. Awarded "EUROKA Innovation of Tomorrow Award" and "ITEA Award of Excellence" in 2018.