A novel DABU-Net model based on principle component analysis for intelligent collaborative robot design

Yu  Jiang

doi:10.6180/jase.202411_27(11).0010

A novel DABU-Net model based on principle component analysis for intelligent collaborative robot design

Electro-Mechanical Engineering

Yu JiangThis email address is being protected from spambots. You need JavaScript enabled to view it.

Shenyang Normal University, No. 253 Huanghe North Street, Shenyang 110034, China

Received: November 5, 2023
Accepted: November 24, 2023
Publication Date: February 7, 2024

Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.6180/jase.202411_27(11).0010

In the traditional space art, the idea of the unity of heaven and man and the connection between heaven and man has been fully affirmed and developed in the long history. In the architectural space, it is often reflected in the geographical location because of the weather, and it should find its own appropriate posture in nature, rather than compete with him. In traditional architectural planning and design, it advocates the organic view of nature that emphasizes the integrity of nature and the internal relationship between things, and pays attention to the combination of Yin and Yang, so as to unify man and nature and self. In particular, image classification plays a very important role in art design, because images are part of art. As the depth of the network deepens, the detail information of the image is lost, which leads to poor segmentation of the edge semantics of objects and objects, and inaccurate prediction of pixel categories in intelligent collaborative robot design. Therefore, this paper proposes a novel DABU-Net model based on principle component analysis for intelligent collaborative robot design. First, we adopt DABU-Net model to extract region of interest in image. Second, the improved channel attention module and spatial attention module extract more important feature details from channel and space respectively. A new image dimensionality reduction algorithm is designed by using principal component analysis, and the algorithm is added to the spatial self-attention module to improve its computing power. Finally, experiments on open data sets show that the proposed method has better segmentation efficiency than other advanced methods.

Keywords: DABU-Net model, principle component analysis, intelligent collaborative robot design, self-attention module

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