Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 8
2515-2519

Deep multiplexing multi-scale features for salient object detection

Zhou Zhiping
Fan Bin
Gai Shan
Xu Wencheng
School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China
DOI: 10.19734/j.issn.1001-3695.2022.01.0033

Abstract

In view of the shortcomings of traditional salient target detection methods in detecting multiple salient targets at different scales, this paper presented a salient object detection algorithm with deep multiplexing of multi-scale features. The network model consisted of vertically stacked bidirectional dense feature aggregation modules and horizontally stacked multi-resolution semantic complementary modules. Firstly, the bidirectional dense feature aggregation module extracted semantic features of different resolutions based on the ResNet backbone network, and then performed adaptive fusion on the top-down and bottom-up paths in turn to obtain multi-scale representation features at different levels. The multi-resolution semantic complementation module fused the multi-scale features of two adjacent levels to eliminate the mutual crosstalk between features at different levels and enhance the consistency of prediction results. The experimental results on 5 benchmark datasets show that the method can achieve the highest Fmax, Sm, MAE of 0.939, 0.921, 0.028, and the detection rate can reach 74.6 fps, which has better detection performance compared with other comparison algorithms.

Foundation Support

国家自然科学基金资助项目(62061032)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.01.0033
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 8
Section: Technology of Graphic & Image
Pages: 2515-2519
Serial Number: 1001-3695(2022)08-048-2515-05

Publish History

[2022-03-30] Accepted Paper
[2022-08-05] Printed Article

Cite This Article

周之平, 樊斌, 盖杉, 等. 多尺度特征深度复用的显著性目标检测算法 [J]. 计算机应用研究, 2022, 39 (8): 2515-2519. (Zhou Zhiping, Fan Bin, Gai Shan, et al. Deep multiplexing multi-scale features for salient object detection [J]. Application Research of Computers, 2022, 39 (8): 2515-2519. )

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.

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