KEMAL KILIÇASLAN

KEMAL KILIÇASLAN

AI Developer

I am Kemal, I live in Ankara and graduated from Kastamonu University, Department of Mathematics in 2022 with a 2.8/4 GPA. I am trying to develop my skills through online courses to apply the fundamental knowledge gained from my mathematics education to the fields of artificial intelligence, machine learning, deep learning and image processing. In the process, I am freelancing, collaborating with various stakeholders and supporting my strategic goals. I am diligently learning the Python programming language and researching algorithms and AI topics, actively interacting with online resources, creating personal projects after completing relevant courses. Due to my interest in image processing, I am also conducting research in these areas and through this consistent effort and dedication, I am developing a strong foundation in AI concepts. The skill set I have acquired allows me to contribute to freelance projects and share what I have learned with others.



Education

Kastamonu Üniversitesi

KASTAMONU UNIVERSITY FACULTY OF SCIENCE AND LITERATURE MATHEMATICS

2022 Graduate - Bachelor's Degree

Personal Initiatives

Kastamonu Üniversitesi Matematik ve Bilim Toplulugu

KASTAMONU UNIVERSITY MATHEMATICS & SCIENCE SOCIETY


(Founding President)

[December 2021 - June 2022]

Kemal Kılıçaslan - My speech on the meaning and importance of the day

'14 March π Day'



Türkiye Matematik Kulübü

Türkiye Matematik Kulübü


(Member)

[December 2020 - ]

I took an active role in the organisation team of 6 events, 4 of which were academic and 2 of which were popular, where we addressed more than 1500 people in total.

Experiences

BİLGİ TEKNOLOJİLERİ VE İLETİŞİM KURUMU

BİLGİ TEKNOLOJİLERİ VE İLETİŞİM KURUMU


AI with Python Trainer

[July 2024 - ]



Calorin

Calorin


Computer Vision Developer

[August 2024 - September 2024]



Tech Skills



Python C++ MATLAB Wolfram Mathematica PostgresSQL HTML5 CSS JavaScript

scikit-learn TensorFlow PyTorch OpenCV BootStrap







PROJECTS



6174 Kaprekar Constant with Python Programming

A 4 digit number with at least one digit different from the one selected by the user is selected, the number 6174 is reached in maximum 7 steps by applying consecutive arithmetic operations.

Face Detection and Person Recognition

It is a face detection and person recognition project on photos, videos and snapshots using Haarcascade classifier algorithm.

Road Lane Lines Detection

It is a project to detect lane lines on roads for autonomous vehicles in which artificial intelligence is actively involved.


Garbage Classification with Convolutional Neural Network (CNN)

Garbage Classification Class
Garbage classification class

Garbage Classification Predicted Class
Garbage classification predicted class

It is a classification project by Stanford University students using Convolutional Neural Network (CNN) model on TrashNet dataset consisting of 6 different classes.

Object Detection and Segmentation with YOLOv8

Object detection & segmentation project from photographs, videos and snapshots with the 8th version of the YOLO algorithm.

Vehicle Recognition with Segmentation Training on a Custom Dataset

It is a project to train the model with segmentation method on 20 randomly selected cars, pickups and trucks and to measure model success on 5 randomly selected cars, pickups and trucks.


Pose Detection with YOLOv8 using Wolfram Mathematica

Microsoft COCO is a pose detection project that uses the latest version of YOLO (You Only Look Once) Version 8, YOLO models developed by Ultralytics in the dataset used for image recognition, segmentation, captioning, object detection and keypoint estimation consisting of more than three hundred thousand images.

Facial Expression Recognition

The FER-2013 dataset created for the Facial Expression Recognition Competition consists of 35887 images with a resolution of 48x48 pixels showing facial expressions corresponding to seven different emotion classes (Angry, Disgust, Fear, Happy, Sad, Surprise and Neutral). 80% of this dataset was used for training and 20% for testing.

Vehicle Speed Estimation

This project uses YOLO for object detection to track vehicles and estimate their speeds. Video frames are processed with thresholds and perspective adjustments via a ViewTransformer class. The output features tracking lines, bounding boxes, and velocity labels, enabling accurate speed estimation and object detection in defined regions.


Traffic Signs Recognition for Turkey

This project detects 17 common traffic signs in city centers for autonomous vehicles using a dataset of screenshots from Google Street View for Turkey and trains the sensitive detection and automation process with the YOLOv8x model on 668 images via Roboflow and creates an automation system for autonomous vehicles.

Data Visualization of Turkey Population with Plotly

It is a data visualization project on the map with line, bar, stack bar, pie, donut charts and choropleth method with male, female and total population data from 1927 to 2023 taken from TURKSTAT using Plotly and Folium libraries.





CERTIFICATES