Performance Comparison and Principle Analysis of Deep Learning-Based Models for Semantic Segmentation

DOI

10.2991/978-94-6463-370-2_65How to use a DOI?

Keywords

Semantic Segmentation; Deep Learning; Computer Vision

Abstract

Nowadays, the concept of artificial intelligence is widely popularized and attracting more and more attention. Computer vision is a hot field of artificial intelligence, and semantic segmentation in computer vision has been a worthwhile research direction in recent years. Not only does it play a crucial role in the current highly focused autonomous driving, but it also has many application scenarios, so it is necessary to study semantic segmentation, The breakthrough in semantic segmentation methods may greatly solve many practical problems currently in use. At present, the main-stream method is semantic segmentation based on deep learning. Compared to traditional machine learning based semantic segmentation methods, it has many advantages, and many excellent researchers are constantly optimizing methods and creating models. Therefore, many models worth learning have emerged during this period. This article will introduce eight semantic segmentation models based on deep learning, analyze the ideas, innovations, and contributions of these methods. After learning and understanding these methods, it may provide new ideas for one's own research and make useful contributions in this field.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yuankai Su
PY  - 2024
DA  - 2024/02/14
TI  - Performance Comparison and Principle Analysis of Deep Learning-Based Models for Semantic Segmentation
BT  - Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)
PB  - Atlantis Press
SP  - 635
EP  - 645
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-370-2_65
DO  - 10.2991/978-94-6463-370-2_65
ID  - Su2024
ER  -