Projects using Cvat in Delhi

Projects using Cvat in DelhiProjects using Cvat in Delhi

Cover image for Annotated computer vision datasets used

Annotated computer vision datasets used for vehicle detection and Automatic Number Plate Recognition (ANPR) systems. The project involved labeling vehicles and number plates in traffic camera footage to help train AI models used in smart city infrastructure, traffic monitoring, and law enforcement systems. Key responsibilities included: • Vehicle detection using bounding box annotation • Number plate annotation for ANPR systems • Dataset preparation for computer vision models • Annotation quality validation and dataset review These datasets support AI models used in traffic monitoring systems, automated toll collection, smart parking systems, and urban mobility analytics.

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Cover image for Annotated CT scan medical imaging

Annotated CT scan medical imaging datasets used to train AI models for healthcare diagnostics and medical image analysis. The project involved identifying and labeling anatomical regions within CT scan images using bounding boxes and segmentation techniques to support machine learning model training. Key tasks included: • Medical image annotation and region labeling • Bounding box annotation for anatomical structures • Dataset preparation for AI model training • Quality control and annotation validation This work supports the development of AI systems used in healthcare diagnostics, medical imaging analysis, and clinical decision support systems.

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Cover image for Annotated complex dental X-ray medical

Annotated complex dental X-ray medical imaging datasets used to train AI models for healthcare applications. The project involved precise labeling of anatomical structures including teeth boundaries, roots, and surrounding regions using polygon and keypoint annotation techniques. The objective was to generate high-quality training datasets that allow machine learning systems to accurately detect dental structures and support medical imaging analysis. Responsibilities included: • Image segmentation and polygon annotation • Keypoint labeling for anatomical structures • Dataset preparation for machine learning models • Annotation quality control and validation This work contributes to the development of AI systems used in medical diagnostics and healthcare imaging analysis.

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