In this piece, we’ll take a plunge into the world of image segmentation using deep learning. We’ll talk about:

• what image segmentation is and the two main types of image segmentation

• Image segmentation architectures

• Loss functions used in image segmentation

• Frameworks that you can use for your image segmentation projects

Let’s dive in.

What is Image Segmentation?

Image Segmentation Architectures

U-Net

FastFCN — Fast Fully-connected network

Gated-SCNN

Mask R-CNN

Image Segmentation Loss functions

Focal Loss

Dice loss

Intersection over Union (IoU)-balanced Loss

Boundary loss

Weighted cross-entropy

Lovász-Softmax loss

Image Segmentation Datasets

Common Objects in COntext — Coco Dataset

PASCAL Visual Object Classes (PASCAL VOC)

The Cityscapes Dataset

The Cambridge-driving Labeled Video Database — CamVid

Image Segmentation Frameworks

Final Thoughts

链接地址：https://towardsdatascience.com/image-segmentation-in-2020-756b77fa88fc