Feature Extraction on the Rail Lines Using Semantic Segmentation and Self-supervised Learning.
-
Updated
Jan 1, 2024 - Python
Feature Extraction on the Rail Lines Using Semantic Segmentation and Self-supervised Learning.
The GitHub repo on "Image Stylization using VGG19" has an implementation of neural style transfer using VGG19, allowing users to apply the style of one image to the content of another. It includes pre-trained models for easy use, enabling users to experiment with different styles and content images for creative and visually appealing results.
A PyTorch project implementing neural style transfer using the VGG19 model, combining the content of one image with the style of another for artistic transformations.
Embark on a machine learning journey with this Python project focusing on automated image classification. The implementation utilizes the VGG19 architecture in Keras, enhancing the model's ability to classify images across 38 different classes. Augmentation techniques like zooming, shearing, and horizontal flipping are employed for a robust dataset
Add a description, image, and links to the vgg19-model topic page so that developers can more easily learn about it.
To associate your repository with the vgg19-model topic, visit your repo's landing page and select "manage topics."