Description
Mastering Image Segmentation with PyTorch, the Mastering Image Segmentation with PyTorch course, is published by Udemy Academy. In this course, you will learn everything you need to know to get started with image segmentation using PyTorch. Image segmentation is a key technology in computer vision that enables computers to understand the content of an image at the pixel level. This technology has many applications including self-driving cars, medical imaging and augmented reality.
This course is designed for both beginners and experts in the field of computer vision. If you’re a beginner, we’ll start with the basics of PyTorch and how to use it for simple modeling. In the following, you will learn how to implement popular semantic segmentation models such as FPN or U-Net. By the end of this course, you will have the skills and knowledge to work on real semantic segmentation projects using PyTorch. Get started now to learn some of the coolest techniques and boost your career with new skills.
What you will learn
- Implementing multi-class semantic segmentation with PyTorch on a real dataset
- Familiarize yourself with different architectures such as UNet, FPN
- Understanding of theoretical background, for example on incremental sampling, loss functions, evaluation criteria
- Perform data preparation to transform inputs into the appropriate format
Who is this course suitable for?
- Developers who want to understand and implement image segmentation
- Data scientists who want to expand the scope of their deep learning techniques
Mastering Image Segmentation with PyTorch course specifications
- Publisher: Udemy
- teacher : Bert Gollnick
- English language
- Education level: Intermediate
- Number of courses: 44
- Training duration: 5 hours and 1 minute
Chapters of the Mastering Image Segmentation with PyTorch course
Course prerequisites
Pictures
Sample video
Installation guide
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download link
File(s) password: www.downloadly.ir
Size
1.9 GB
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