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Static Target Recognition of Indoor Mobile Robot Based on Improved SSD Algorithm

Published: 30 May 2020 Publication History

Abstract

In the indoor application environment, in order to improve the overall efficiency of the service robot in the target detection, combined with the deep learning target detection theory, the SSD target detection algorithm and a lightweight neural network mobilenetv2 are combined to design a new target detection algorithm, which improves the target detection efficiency to a certain extent. The main improvements of this paper are as follows. Firstly, using SSD for reference, multi-scale feature extraction is carried out for the target image, and different sizes of targets are detected at different scales; Secondly, in the process of matching the actual target detection region with the algorithm prediction region, the positive and negative samples are processed properly to ensure the stability of the model; Thirdly, using the idea of mobilenet for reference, the traditional convolution is replaced by the deep separable convolution, which greatly reduces the calculation of data processing and improves the processing speed of the model while ensuring the accuracy of the model. Fourthly, in view of the time-consuming and laborious situation of manually marking data sets, a method of automatically marking data sets is proposed, which improves the efficiency of data set preparation and reduces the workload of manual marking. Through the improvement of the above algorithm, the detection speed of the system model has been greatly improved compared with SSD algorithm, and the overall recognition efficiency of indoor service robot has been improved to a certain extent.

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  • (2020)Mask wearing detection method based on SSD-Mask algorithm2020 International Conference on Computer Science and Management Technology (ICCSMT)10.1109/ICCSMT51754.2020.00034(138-143)Online publication date: Nov-2020

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ICITEE '19: Proceedings of the 2nd International Conference on Information Technologies and Electrical Engineering
December 2019
870 pages
ISBN:9781450372930
DOI:10.1145/3386415
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 30 May 2020

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Author Tags

  1. Indoor target recognition
  2. Mobilenetv2
  3. Multiscale features
  4. SSD model

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  • (2020)Mask wearing detection method based on SSD-Mask algorithm2020 International Conference on Computer Science and Management Technology (ICCSMT)10.1109/ICCSMT51754.2020.00034(138-143)Online publication date: Nov-2020

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