Successfully developed an object detection model using Faster R-CNN to detect and localize wind turbines in aerial imagery, aiding in automated monitoring and infrastructure assessment.

Successfully developed an instance segmentation model using Mask R-CNN to detect and segment brain tumors from MRI scans with pixel-level precision.

Successfully developed an object detection model using Faster R-CNN to detect safety helmets and ensure compliance at construction sites by accurately localizing helmets and personnel in real-time images.

This repository provides topics in PyTorch which is used for Deep Learning

Developed an instance segmentation model using Mask R-CNN to accurately identify and segment germinated seeds in high-resolution seed images.

Successfully developed an object detection model using Faster R-CNN to detect vehicles and traffic-related objects in real-time road scenes, supporting smart traffic monitoring and surveillance applications.

Successfully developed an object detection model using Faster R-CNN to detect and classify traffic signs in road images, enhancing autonomous driving and intelligent transportation systems.

Successfully developed a wildlife detection model using Faster R-CNN to identify and localize animals in natural habitats, supporting conservation efforts and ecological research.

AI/ML Trained Image Recognition for Finnish trees in Python with Gradio Web Interface