Deep Learning Segmentation: Backbone Networks and Advancements - A Comprehensive Overview

In recent years, segmentation methods based on deep learning have made significant advancements. These methods leverage deep learning techniques to directly learn and extract image features from the data. The backbone networks utilized in deep learning-based segmentation methods primarily consist of convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), Transformer, and other similar architectures. These backbone networks play a crucial role in the success of segmentation methods by enabling efficient and accurate extraction of image features.