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I will create a full computer vision ai solution with API and cloud integration
Electronics and AI Intern
I am an Electrical Engineering student specializing in the intersection of hardware and intelligence. I build end-to-end solutions that bring AI to the edge.
Expertise:
Computer Vision: YOLO, U-Net,...
About this Gig
Full Computer Vision AI Solution: From Data to Deployment
Need a production-ready AI? I provide a complete Computer Vision pipelinefrom dataset preparation to cloud deployment. Whether you need object detection or pixel-level segmentation, I deliver high-performance solutions.
Core Specializations:
- Object Detection: Fast detection using YOLO (v8-v11) or Faster R-CNN.
- Image Segmentation: Pixel-perfect results using U-Net, DeepLabV3+, or Mask R-CNN (ideal for medical/industrial use).
- Classification: Custom CNN architectures for high-accuracy sorting.
Whats Included:
- Data Prep: Cleaning & annotation (up to 200 images).
- Model Engineering: SOTA architectures via PyTorch/TensorFlow.
- Optimization: Fine-tuning for high accuracy & low latency.
- Deployment: Cloud hosting (AWS/GCP/Azure) & API integration.
- Handoff: Well-documented source code & technical guide.
Important Notes:
- Dataset: Base price covers 200 images. Larger sets require Gig Extras.
- Cloud Fees: Clients cover their own hosting costs.
- Revisions: Includes 1 revision for fine-tuning. Structural changes after training start require an extraa.
- Please message me before ordering to discuss your project!
FAQ
What do I receive at the end of the project?
You will receive the fully trained model weights, well-commented source code (Python), documentation on how to run it, and—if selected—the API endpoint or cloud-deployed environment ready for use.
Can you work with my specific dataset?
Yes! I can work with images, videos, or live streams. My base package includes labeling for up to 200 images. If you have a larger dataset or need complex video annotation, please message me for a custom quote.
Who covers the costs for Cloud Deployment?
I handle the technical setup and integration on platforms like AWS, GCP, or Azure. However, the recurring subscription or usage fees for the cloud hosting itself are the responsibility of the client. I can recommend the most cost-effective tier for your project!
What is the difference between YOLO and U-Net/DeepLabV3?
YOLO is designed for Object Detection, where we draw "bounding boxes" around objects for speed and real-time use. U-Net and DeepLabV3+ are for Semantic Segmentation, providing pixel-perfect masks for high-precision tasks like medical imaging or satellite analysis. I wll help you chose right one.
