Hybrid YOLOv9-DETR (Master’s Thesis)
Hybrid object detection for strawberry disease & ripeness across 9k+ images. ~90% detection accuracy using YOLOv9 + DETR.
- Python
- PyTorch
- YOLOv9
- DETR
- Colab
Hi, I’m Amir , a Master of Computing graduate passionate about building digital solutions that blend web development, machine learning, and cloud computing. I enjoy turning ideas into scalable applications, whether that’s through responsive websites, intelligent AI models, or efficient cloud deployments.
I bring a strong foundation in frontend and backend development, experience in AI-driven projects , and a curious mindset that drives me to keep learning. My goal is to create user-focused technology that makes a real-world impact. Feel free to Connect or Follow me on my Linkedin and Github where we can connect and share our ideas.
I'm open to Job opportunities where I can contribute, learn and grow. If you have a good opportunity that matches my skills and experience then don't hesitate to contact me.
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Hybrid object detection for strawberry disease & ripeness across 9k+ images. ~90% detection accuracy using YOLOv9 + DETR.
Raspberry Pi + sensors streaming temperature, humidity, and air quality to real-time dashboards via Node-RED.
Analysis of cloud architecture, scalability, cost optimizations, and security trade-offs across AWS/Azure paradigms.