Deep Learning with PyTorch : Image Segmentation
In this 2-hour project-based course, you will be able to : - Understand the Segmentation Dataset and you will write a custom dataset class for Image-mask dataset. Additionally, you will apply segmentation augmentation to augment images as well as its masks. For image-mask augmentation you will use albumentation library. You will plot the image-Mask pair. - Load a pretrained state of the art convolutional neural network for segmentation problem(for e.g, Unet) using segmentation model pytorch library.
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- المدة 3 ساعات hours
- الطبع بواسطة Coursera Project Network
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In this 2-hour project-based course, you will be able to : - Understand the Segmentation Dataset and you will write a custom dataset class for Image-mask dataset. Additionally, you will apply segmentation augmentation to augment images as well as its masks. For image-mask augmentation you will use albumentation library. You will plot the image-Mask pair. - Load a pretrained state of the art convolutional neural network for segmentation problem(for e.g, Unet) using segmentation model pytorch library. - Create train function and evaluator function which will helpful to write training loop. Moreover, you will use training loop to train the model.الوحدات
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Dive into "Deep Learning with PyTorch: Image Segmentation," an intermediate-level, project-based course designed for IT and Computer Science enthusiasts. Guided by expert instruction from Coursera, this 2-hour course teaches you to understand segmentation datasets, apply image-mask augmentation, and utilize state-of-the-art convolutional neural networks like Unet. Perfect for those looking to enhance their deep learning skills, the course offers free subscription options.
Parth Dhameliya