https://github.com/kmohamedalie/u-nets_imagesegmentation

Coursera - Deep Learning with PyTorch : Image Segmentation 🖼️
https://github.com/kmohamedalie/u-nets_imagesegmentation

coursera deep-learning image-segmentation u-net

Last synced: about 1 month ago
JSON representation

Coursera - Deep Learning with PyTorch : Image Segmentation 🖼️

• Host: GitHub
• URL: https://github.com/kmohamedalie/u-nets_imagesegmentation
• Owner: Kmohamedalie
• Created: 2024-06-24T14:35:20.000Z (6 months ago)
• Default Branch: master
• Last Pushed: 2024-06-30T22:09:15.000Z (6 months ago)
• Last Synced: 2024-07-04T23:40:26.492Z (6 months ago)
• Topics: coursera, deep-learning, image-segmentation, u-net
• Language: Jupyter Notebook
• Homepage:
• Size: 1.05 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Deep Learning with PyTorch : Image Segmentation 🖼️

Instructor: [Parth Dhameliya](https://www.coursera.org/instructor/~42281109)

**[Image Segmentation](https://www.ibm.com/topics/image-segmentation#:~:text=Image%20segmentation%20is%20a%20computer,faster%2C%20more%20advanced%20image%20processing.):** Image segmentation is a computer vision technique that partitions a digital image into discrete groups of pixels—image segments—to inform object detection and related tasks. By parsing an image’s complex visual data into specifically shaped segments, image segmentation enables faster, more advanced image processing.

**[U-Nets](https://www.ibm.com/topics/image-segmentation#:~:text=Image%20segmentation%20is%20a%20computer,faster%2C%20more%20advanced%20image%20processing.):** U-Nets modify FCN architecture to reduce data loss during downsampling with skip connections, preserving greater detail by selectively bypassing some convolutional layers as information and gradients move through the neural network. Its name is derived from the shape of diagrams demonstrating the arrangement of its layers.







**[Applications:](https://deeplobe.ai/image-segmentation-the-most-interesting-applications/)**  Medical Imaging, Autonomous Vehicles, Agriculture(weed detection).







![image](https://github.com/Kmohamedalie/U-Nets_ImageSegmentation/assets/63104472/9c146f68-a26f-4715-8630-62f606b469b5)







## **DEMO:**

https://github.com/Kmohamedalie/U-Nets_ImageSegmentation/assets/63104472/5c3fa29f-a3c6-4c07-a419-c4989b9c55c0