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I will build models for computer vision and image processing tasks
Building Smart AI Solutions That Turn Data into Real Impact!
AI/ML Developer specializing in Computer Vision with deep expertise in solving real-world problems using cutting-edge tools. I've built high-impact solutions like brain tumor detection, hand gesture r...
Über diesen Service
Welcome! Im a seasoned Computer Vision Engineer delivering enterprise-grade AI solutions for businesses, startups, and research.
I specialize in Custom Object Detection, Pose Estimation, OCR, Image Segmentation, and Model Deployment across cloud, mobile, and edge devices.
I work with PyTorch, TensorFlow, Keras, YOLOv5/v8, Faster R-CNN, EfficientDet, Detectron2, TensorRT, ONNX, OpenVINO, TensorFlowLite, CoreML, TorchScript, and more.
Services Offered:
- Object Detection (Images, Videos, Real-Time)
- Pose Estimation (Pitch, Yaw, Roll Detection)
- OCR and Text Extraction
- Medical Imaging, Drone, and Industrial Analysis
- API Development (Flask/FastAPI) + Docker/Kubernetes
Deployment Targets:
- AWS EC2, GCP, Azure
- Android (TensorFlowLite), iOS (CoreML)
- Raspberry Pi, Jetson Nano/Xavier, OpenVINO
Tools & Technologies I Use:
- OpenCV, Scikit-Image, Roboflow, LabelImg, MLflow, TensorBoard, PyCharm, Jupyter Notebooks, Docker, Colab, GitHub
Contact me before placing an order to discuss your project, timeline, and pricing.
Lets build world-class Computer Vision systems that deliver real impact!
Mein Portfolio
FAQ
What kind of custom models do you build?
I build custom object detection models (for images and videos), pose estimation models, OCR solutions, and image segmentation for various applications including medical imaging, drones, industrial use, and more.
What technologies and frameworks do you use?
I work with top-tier frameworks and libraries like PyTorch, TensorFlow, YOLOv5/v8, Keras, OpenCV, EfficientDet, TensorFlowLite, CoreML, ONNX, TensorRT, and more. I also use tools like Docker, Kubernetes, and Flask/FastAPI for deployment and scalability.
Can you deploy models to edge devices like Raspberry Pi or Jetson Nano?
Yes! I specialize in deploying models to edge devices such as Raspberry Pi, Jetson Nano, Coral Edge TPU, and other low-power devices using OpenVINO or TensorFlowLite for efficient inference.
Will I receive the code and model files after delivery?
Absolutely! You’ll receive the trained model and source code in a well-documented, easy-to-understand format, along with deployment instructions and any additional requirements for setting up the model in your environment.
Do you provide API development and deployment?
Yes, I offer API development using FastAPI or Flask and can deploy them to AWS EC2, GCP, or Azure for scalable solutions. I also provide Docker containers and Kubernetes orchestration for production-ready services.
Can you deploy my model to mobile devices?
Yes, I can optimize and deploy models to Android (TensorFlowLite) and iOS (CoreML), making them ready for real-time inference on mobile platforms.
What’s the process for working with you?
Step 1: Contact me to discuss your project. Step 2: We’ll finalize the requirements, cost, and timeline. Step 3: I’ll deliver a prototype or a working model, followed by testing and deployment.
Do you offer post-delivery support?
Yes! I offer limited post-delivery support to ensure the model performs well in the production environment and to help with any setup or troubleshooting.
