In accordance with regulations and requirements, the editorial department's website domain has been changed to arocmag.cn. The original domain (arocmag.com) will be discontinued after Dec. 31st, 2024.
See More
App. Res. of Comp. Accepted Paper
Vol. 41, 2024 No. 11

Active learning semantic segmentation model based on improved double deep q network

Li Lin
Liu Zheng
Nan Hai
Zhang Zewei
Wei Ye
College Of Computer Science And Engineering, Chongqing University of Technology, Chongqing 400054, China
DOI: 10.19734/j.issn.1001-3695.2024.02.0070

Abstract

This paper proposed an active learning semantic segmentation model named CG_D3QN, based on an improved dual deep Q-network, to address the challenges of acquiring pixel labels and class imbalances in image semantic segmentation tasks. The model used a hybrid network structure that integrates a dueling network architecture with gated recurrent units. This structure alleviated the overestimation of Q-values and efficiently utilized historical state information, thereby improving the accuracy and computational efficiency of policy evaluation. On the CamVid and Cityscapes datasets, the algorithm reduced the required sample annotation volume by 65.0% and enhanced the mean Intersection over Union by approximately 1% to 3% for classes with fewer sample labels. Experimental results show that the model significantly reduced the cost of sample annotations and effectively mitigated class imbalance issues, while being adaptable to different segmentation networks.

Foundation Support

重庆市教育委员会科学技术研究项目(KJQN202101149)
重庆市基础研究与前沿探索专项(CSTB2022NSCQ-MSX0918,CSTB2022NSCQ-MSX0493)
重庆理工大学研究生创新资助项目(gzlcx20233251)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.02.0070
Publish at: Application Research of Computers Accepted Paper, Vol. 41, 2024 No. 11

Publish History

[2024-05-21] Accepted Paper

Cite This Article

李林, 刘政, 南海, 等. 基于改进双重深度Q网络的主动学习语义分割模型 [J]. 计算机应用研究, 2024, 41 (11). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.02.0070. (Li Lin, Liu Zheng, Nan Hai, et al. Active learning semantic segmentation model based on improved double deep q network [J]. Application Research of Computers, 2024, 41 (11). (2024-09-11). https://doi.org/10.19734/j.issn.1001-3695.2024.02.0070. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)