A Systematic Literature Review on Machine Learning and Deep Learning Methods for Semantic Segmentation-Reference-Cited by-同舟云学术

A Systematic Literature Review on Machine Learning and Deep Learning Methods for Semantic Segmentation

Author:

Sohail Ali¹^ORCID,Nawaz Naeem A.²^ORCID,Shah Asghar Ali³^ORCID,Rasheed Saim⁴^ORCID,Ilyas Sheeba¹,Ehsan Muhammad Khurram⁵^ORCID

Affiliation:

1. Department of Computer Science, Minhaj University Lahore, Lahore, Pakistan

2. College of Computer and Information Systems, Umm Al-Qura University, Makkah Al-Mukarramah, Saudi Arabia

3. Department of Computer Science, Bahria University, Lahore Campus, Lahore, Pakistan

4. Department of Information Technology, Faculty of Computing and IT, King Abdulaziz University, Jeddah, Saudi Arabia

5. Faculty of Engineering Sciences, Bahria University, Lahore Campus, Lahore, Pakistan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

Reference62 articles.

1. SegNet: A deep convolutional encoder–decoder architecture for robust semantic pixel-wise labelling;badrinarayanan;arXiv 1505 07293,2015

Cited by 23 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

5. Innovative Crop Mapping in Hawaii: The First 10Meter Resolution Cropland Data Layers for 2023;2024 12th International Conference on Agro-Geoinformatics (Agro-Geoinformatics);2024-07-15