JSAI2024

Presentation information

General Session

General Session » GS-2 Machine learning

[2D4-GS-2] Machine learning: Image recognition

Wed. May 29, 2024 1:30 PM - 3:10 PM Room D (Temporary room 2)

座長:山口 真弥(日本電信電話株式会社)

1:50 PM - 2:10 PM

[2D4-GS-2-02] Handwritten Character Recognition and Image Classification using Neural Cellular Automata

〇Kotaro Nakai1, Chiaki Sakama1 (1. Faculty of Systems Engineering, Wakayama University)

Keywords:Image Recognition, Neural Cellular Automata

Neural Cellular Automata (NCA) are a computational model that incorporates neural networks into the update rules ofcellular automata. In this study, we introduce three different types of NCA modes for handwritten character recognition andimage classification. We evaluate their performance using four different datasets: MNIST, fashionMNIST, CIFAR-10 andETL-8. The experimental results show that the proposed systems successfully recognize handwritten characters and classifyimages. Moreover, it is shown that the NCA models exhibit higher performance than the CNN model when learning fromsmall data.

Authentication for paper PDF access

A password is required to view paper PDFs. If you are a registered participant, please log on the site from Participant Log In.
You could view the PDF with entering the PDF viewing password bellow.

Password