Multimodal Deep Learning in Semantic Image Segmentation: A Review

被引:4
|
作者
Raman, Vishal [1 ]
Kumari, Madhu [1 ]
机构
[1] NIT Hamirpur, Hamirpur, Himachal Prades, India
来源
PROCEEDINGS OF 2018 INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND INTERNET OF THINGS (CCIOT 2018) | 2018年
关键词
Multimodal learning; semantic image segmentation; deep learning; NETWORKS;
D O I
10.1145/3291064.3291067
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In recent years, there has been a lot of research in the area of semantic image segmentation, which involves breaking down an image into its discrete components, such that humans can give meaning to its contents. From the humble beginnings of image search using human-provided captions, content-based image retrieval has come a long way. Yet, areas of research and improvement are far from diminishing. In this paper we will take a look at how multi-modal approaches to semantic image segmentation are setting the new standard in image search and retrieval.
引用
收藏
页码:7 / 11
页数:5
相关论文
共 50 条
  • [31] Features to Text: A Comprehensive Survey of Deep Learning on Semantic Segmentation and Image Captioning
    Oluwasammi, Ariyo
    Aftab, Muhammad Umar
    Qin, Zhiguang
    Son Tung Ngo
    Thang Van Doan
    Son Ba Nguyen
    Son Hoang Nguyen
    Giang Hoang Nguyen
    COMPLEXITY, 2021, 2021
  • [32] Combining deep learning and ontology reasoning for remote sensing image semantic segmentation
    Li, Yansheng
    Ouyang, Song
    Zhang, Yongjun
    KNOWLEDGE-BASED SYSTEMS, 2022, 243
  • [33] Deep semantic segmentation of natural and medical images: a review
    Asgari Taghanaki, Saeid
    Abhishek, Kumar
    Cohen, Joseph Paul
    Cohen-Adad, Julien
    Hamarneh, Ghassan
    ARTIFICIAL INTELLIGENCE REVIEW, 2021, 54 (01) : 137 - 178
  • [34] Deep semantic segmentation of natural and medical images: a review
    Saeid Asgari Taghanaki
    Kumar Abhishek
    Joseph Paul Cohen
    Julien Cohen-Adad
    Ghassan Hamarneh
    Artificial Intelligence Review, 2021, 54 : 137 - 178
  • [35] A review of deep learning methods for semantic segmentation of remote sensing imagery
    Yuan, Xiaohui
    Shi, Jianfang
    Gu, Lichuan
    EXPERT SYSTEMS WITH APPLICATIONS, 2021, 169
  • [36] Understanding Deep Learning Techniques for Image Segmentation
    Ghosh, Swarnendu
    Das, Nibaran
    Das, Ishita
    Maulik, Ujjwal
    ACM COMPUTING SURVEYS, 2019, 52 (04)
  • [37] Image Segmentation Using Deep Learning: A Survey
    Minaee, Shervin
    Boykov, Yuri Y.
    Porikli, Fatih
    Plaza, Antonio J.
    Kehtarnavaz, Nasser
    Terzopoulos, Demetri
    IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2022, 44 (07) : 3523 - 3542
  • [38] Image Segmentation of a Sewer Based on Deep Learning
    He, Min
    Zhao, Qinnan
    Gao, Huanhuan
    Zhang, Xinying
    Zhao, Qin
    SUSTAINABILITY, 2022, 14 (11)
  • [39] Semantic Guided Deep Unsupervised Image Segmentation
    Saha, Sudipan
    Sudhakaran, Swathikiran
    Banerjee, Biplab
    Pendurkar, Sumedh
    IMAGE ANALYSIS AND PROCESSING - ICIAP 2019, PT II, 2019, 11752 : 499 - 510
  • [40] A review of the application of deep learning in medical image classification and segmentation
    Cai, Lei
    Gao, Jingyang
    Zhao, Di
    ANNALS OF TRANSLATIONAL MEDICINE, 2020, 8 (11)