https://github.com/tanishkamarrott/semantic-segmentation-using-unet

Semantic Segmentation using U-Net -Conceptualised a Semantic Segmentation model using the U-Net Architecture. -Trained a convolutional neural network to perform fast and precise segmentation of images by outputting a pixel-wise mask using the modified U-Net, achieving an accuracy of 97%
https://github.com/tanishkamarrott/semantic-segmentation-using-unet

Last synced: 4 months ago
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Semantic Segmentation using U-Net -Conceptualised a Semantic Segmentation model using the U-Net Architecture. -Trained a convolutional neural network to perform fast and precise segmentation of images by outputting a pixel-wise mask using the modified U-Net, achieving an accuracy of 97%

• Host: GitHub
• URL: https://github.com/tanishkamarrott/semantic-segmentation-using-unet
• Owner: TanishkaMarrott
• Created: 2021-08-03T09:43:41.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2021-08-03T09:44:51.000Z (about 4 years ago)
• Last Synced: 2025-03-22T14:24:19.197Z (7 months ago)
• Language: Jupyter Notebook
• Size: 3.4 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Semantic-Segmentation-using-UNet

Semantic Segmentation using U-Net 

Deep Learning Frameworks used: Python, Keras, TensorFlow

-Conceptualised a Semantic Segmentation model using the U-Net Architecture.

-Trained a convolutional neural network to perform fast and precise segmentation of images by outputting a pixel-wise mask using the modified U-Net, achieving an accuracy of 97%