Development of a mobile application for marking goods in a warehouse; writing a parser for collecting OEM numbers (Original Equipment Market) of stock car parts; had experience in developing an autoencoder with a convolutional neural network to bypass captcha; development of a desktop application in python using the pyqt5 graphics library to create a descriptive base of all products in the stock

Mentor of the "Self-driving car on Unity" project for students of the Suleiman Demirel University. The aim of the projects was to show students how to apply the acquired knowledge in practice. At the beginning, we discussed with the students the implementation of the project and all the details. It was decided to do the project on the Unity engine using Learning with a teacher. These decisions are related to the fact that students already knew and had little experience with these technologies. After discussion, the group of 5 students was divided into 2 teams: the Unity team and the AI team. The Unity team was tasked with implementing an environment with a controlled object (car), control was carried out through data transfer using sockets over the TCP protocol. the control facility housed a camera almost perpendicular to the road and a lidar. The task of the lidar is to capture three road conditions: 1. Free path; 2. There is a pedestrian in front; 3. Any static obstacle. The AI team had to develop a 2-component convolutional neural network: the 1st part of the network receives data from the camera as input, the 2nd part receives data from the lidar. The environmental conditions are as follows: 1.2-lane shape-shifting road 2.2 kinds of obstacles, pedestrian and car 3.pedestrians move and cross 2 lanes The behavior algorithm is as follows: 1. if the road is clear of objects and straight, then go straight; 2. if the road is free of objects but there is a left / right turn, then turn left / right; 3.If there is a pedestrian in front, then stop until the pedestrian passes 4.If there is an obstacle in front, then go around the free lane You can find the whole project at https://github.com/meiirbergali24/Self-Driving-CarProject

Writing software for vehicle slope sensors, assembling electromyography sensors and further data collection for the analysis and classification of limb gestures

Documentation and revision of existing code

KIT, Master’s Degree Вычислительная техника и программное обеспечение (ВТиПО)

Информационных технологий, Вычислительная техника и программное обеспечение (ВТиПО)