Mehmet Ali Güven

A comprehensive autonomous robot control system developed in C++ for robotics and embedded systems. This project combines artificial intelligence and systems engineering techniques.

A secure, offline voice control system for robots that combines biometric voice authentication with speech recognition using Resemblyzer and Vosk.

A real-time human detection and tracking system designed for the LITE3 quadruped robot using YOLO11 on Rockchip NPU (RK3588).

An intelligent tracking system that uses YOLOv5 for person detection and RealSense depth camera for obstacle avoidance.

Extracts visual features and detects moving objects to understand motion patterns and object movements in video content.

Analyzes real-time video feeds from security cameras to detect weapons and provide necessary alerts.

AI-powered system that uses deep learning to automatically detect abnormal behaviors in real-time CCTV footage.

Machine learning project that detects diseases from OCT (Optical Coherence Tomography) images without assistance.

Uses YOLO to detect objects and performs keyword-based web searches to analyze and present relevant information.

Adds subtitles by translating text in videos into desired languages using an OCR model.

Translates microphone recordings instantly into the desired language and provides audio output.

Script for matching datasets and frames in CVAT using MD5 for automated tagging.