Endoscopy Image Retrieval by Mixer Multi-Layer Perceptron
Quoc-Huy Trinh, Minh-Van Nguyen
Citation: Position and Communication Papers of the 16th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 26, pages 223–226 (2021)
Abstract. In Computer Vision, the Image Retrieval task is one of the interests of researchers, particularly medical image retrieval and endoscopy images. With the development of the Convolution Neural Network and Vision Transformer Technique, there are many proposals for using these techniques to make Image Retrieval Task and achieve a competitive result. In this paper, we propose a method that using Mixer Multi-Layer Perceptron architecture (Mixer-MLP) to build an Image Retrieval System with Medical images, particularly Endoscopic Images. This System base on the Classification process of Mixer-MLP architecture to generate vector representation for similarity cal- culation. The research result achieves competitively with efficient training time.
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