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Deep Learning with PyTorch : Image Segmentation に戻る

Coursera Project Network による Deep Learning with PyTorch : Image Segmentation の受講者のレビューおよびフィードバック



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....



Deep Learning with PyTorch : Image Segmentation : 1 - 6 / 6 レビュー

by Ye Y


Great instructor and very practical hands-on approach. I would prefer more explanation on other encoder and weight presets as that will be important for transferring the knowledge learned here!

by Shane M


Pretty good overall. Some work needed with this projects to make them easier to debug, such as making source code available with a diff tool so people can more easily pick out stupid types.

Because this is python, not cpp or java or similar, it can actually be pretty hard to catch a lot of typos, due to lack of compile time checks, scope control, and abundance of global variables.

by Halil U


it is too much step by step follow. it does not explain the why about what is happening within the project.

being said that, it is good for just getting started.

by Abdelkader M



by vaghani r d



by Mohammed A


As a course it didnot explain professionally.