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

被引:0
|
作者
Sohail, Ali [1 ]
Nawaz, Naeem A. [2 ]
Shah, Asghar Ali [3 ]
Rasheed, Saim [4 ]
Ilyas, Sheeba [1 ]
Ehsan, Muhammad Khurram [5 ]
机构
[1] Minhaj University Lahore, Department of Computer Science, Lahore,54782, Pakistan
[2] Umm Al-Qura University, College of Computer and Information Systems, Makkah Al-Mukarramah,24381, Saudi Arabia
[3] Bahria University, Department of Computer Science, Lahore Campus, Lahore,54782, Pakistan
[4] King Abdulaziz University, Faculty of Computing and IT, Department of Information Technology, Jeddah,21589, Saudi Arabia
[5] Bahria University, Faculty of Engineering Sciences, Lahore Campus, Lahore,54782, Pakistan
来源
IEEE Access | 2022年 / 10卷
关键词
Deep learning - Digital libraries - Learning algorithms - Neural networks - Reviews - Semantic Segmentation - Semantic Web;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
页码:134557 / 134570
相关论文
共 50 条
  • [31] Visual SLAM Integration With Semantic Segmentation and Deep Learning: A Review
    Pu, Huayan
    Luo, Jun
    Wang, Gang
    Huang, Tao
    Liu, Hongliang
    Luo, Jun
    IEEE SENSORS JOURNAL, 2023, 23 (19) : 22119 - 22138
  • [32] Review of Semantic Segmentation of Point Cloud Based on Deep Learning
    Zhang Jiaying
    Zhao Xiaoli
    Chen Zheng
    LASER & OPTOELECTRONICS PROGRESS, 2020, 57 (04)
  • [33] Literature review on deep learning for the segmentation of seismic images
    Monteiro, Bruno A. A.
    Cangucu, Gabriel L.
    Jorge, Leonardo M. S.
    Vareto, Rafael H.
    Oliveira, Bryan S.
    Silva, Thales H.
    Lima, Luiz Alberto
    Machado, Alexei M. C.
    Schwartz, William Robson
    Vaz-de-Melo, Pedro O. S.
    EARTH-SCIENCE REVIEWS, 2024, 258
  • [34] Machine Learning and Deep Learning Approaches for Arabic Sign Language Recognition: A Decade Systematic Literature Review
    Alayed, Asmaa
    SENSORS, 2024, 24 (23)
  • [35] Evaluating online health information quality using machine learning and deep learning: A systematic literature review
    Baqraf, Yousef Khamis Ahmed
    Keikhosrokiani, Pantea
    Al-Rawashdeh, Manal
    DIGITAL HEALTH, 2023, 9
  • [36] The future of skin cancer diagnosis: a comprehensive systematic literature review of machine learning and deep learning models
    Adamu, Shamsuddeen
    Alhussian, Hitham
    Aziz, Norshakirah
    Abdulkadir, Said Jadid
    Alwadin, Ayed
    Imam, Abdullahi Abubakar
    Abdullahi, Mujaheed
    Garba, Aliyu
    Saidu, Yahaya
    COGENT ENGINEERING, 2024, 11 (01):
  • [37] A systematic literature review of software effort prediction using machine learning methods
    Ali, Asad
    Gravino, Carmine
    JOURNAL OF SOFTWARE-EVOLUTION AND PROCESS, 2019, 31 (10)
  • [38] Applications of machine learning methods in port operations-A systematic literature review
    Filom, Siyavash
    Amiri, Amir M.
    Razavi, Saiedeh
    TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2022, 161
  • [39] Traditional Machine Learning Methods versus Deep Learning for Meningioma Classification, Grading, Outcome Prediction, and Segmentation: A Systematic Review and Meta-Analysis
    Maniar, Krish M.
    Lassaren, Philipp
    Rana, Aakanksha
    Yao, Yuxin
    Tewarie, Ishaan A.
    Gerstl, Jakob V. E.
    Blanco, Camila M. Recio
    Power, Liam H.
    Mammi, Marco
    Mattie, Heather
    Smith, Timothy R.
    Mekary, Rania A.
    WORLD NEUROSURGERY, 2023, 179 : E119 - E134
  • [40] Deforestation detection using deep learning-based semantic segmentation techniques: a systematic review
    Jelas, Imran Md
    Zulkifley, Mohd Asyraf
    Abdullah, Mardina
    Spraggon, Martin
    FRONTIERS IN FORESTS AND GLOBAL CHANGE, 2024, 7