Endoscopy image retrieval by Mixer Multi-Layer Perceptron

• Autorzy: Trinh Quoc-Huy , Nguyen Minh-Van

Identyfikatory

DOI

10.15439/2021F145

• Konferencja: Federated Conference on Computer Science and Information Systems (16 ; 02-05.09.2021 ; online)
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

medical image retrieval; convolution neural network; content-based Image retrieval; feature extraction

PL

odzyskiwanie obrazów medycznych; splotowa sieć neuronowa; wyszukiwanie obrazów na podstawie treści; ekstrakcja cech

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2021
• Tom: Vol. 26
• Strony: 223--226
• Opis fizyczny: Bibliogr. 18 poz., il.

Twórcy

autor

Trinh Quoc-Huy

• University of Science, VNU-HCM, Vietnam Vietnam National University, Ho Chi Minh City, Vietnam

autor

Nguyen Minh-Van

• University of Science, VNU-HCM, Vietnam Vietnam National University, Ho Chi Minh City, Vietnam

Bibliografia

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Uwagi

1. This research is supported by research funding from Faculty of Information Technology, University of Science, Vietnam National University - Ho Chi Minh City

2. Track 5: Young Researchers Workshop on Artificial Intelligence and Cybersecurity