🎯 Computer Vision Engineer | AI Enthusiast | Deep Learning Specialist I'm a Computer Vision Engineer with over two years of experience in AI and deep learning. My work primarily focuses on building and optimizing computer vision models for real-world applications, specializing in tasks such as object detection, real-time video analysis, and edge deployment. I have hands-on experience with various AI frameworks and enjoy tackling complex challenges to create impactful solutions.
A computer vision-based tennis and MMA smart coach that extracts statistics and provides recommendations from match videos, using advanced techniques like TrackNet, custom-built CNNs, YOLO, image processing, and homography.
Built a multi-modal assistant integrating computer vision, speech recognition, and NLP. Fine-tuned models for Egyptian dialect recognition and utilized Ccomputer Vision for emotion detection, enhancing user interaction through personalized responses.
A tool to extract detailed game statistics, utilizing YOLOv3 for high-precision detection of players, ball, and goal, along with key statistics like distance covered, possession, shots, and passes.
Detects and reads license plates in video streams, associating detected plates with vehicles using a custom-trained model and PaddleOCR for content recognition.
This project implements a Pix2Pix GAN using PyTorch to generate maps from satellite images.
Implemented a YOLOv8-based system to monitor crowd behavior in real-time, measuring social distancing violations with customizable visualization settings.
📫 Connect with Me Email: ahmed.mshafiq77@gmail.com