Successfully developed an instance segmentation model using Mask R-CNN to detect and segment brain tumors from MRI scans with pixel-level precision.
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Updated
Jul 4, 2025 - Jupyter Notebook
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.
AI/ML Trained Image Recognition for Finnish trees in Python with Gradio Web Interface
This repository provides topics in PyTorch which is used for Deep Learning
Successfully developed a wildlife detection model using Faster R-CNN to identify and localize animals in natural habitats, supporting conservation efforts and ecological research.
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 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 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.
Developed an instance segmentation model using Mask R-CNN to accurately identify and segment germinated seeds in high-resolution seed images.
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