Han Hye Rim Jo, Jeonghee 박종길 Park, Seongsik 2024-01-12T02:46:07Z 2024-01-12T02:46:07Z 2023-10-30 2023-06 https://pubs.kist.re.kr/handle/201004/76434 https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11522582 Multimodal models have been studied as promising model that can overcome the disadvantages of the unimodal models. However, not much research has been conducted on the effectiveness of multimodality in spiking neural networks (SNNs), which have been considered a next-generation artificial neural network for their energy efficiency. Thus, in this paper, we analyzed the effectiveness through experiments on modality, model size, and noise. According to our analysis, we validated that SNNs showed greater effectiveness in multimodality than DNNs. Korean (사)대한전자공학회 멀티모달 스파이킹 뉴럴 네트워크의 성능 분석 Performance Analysis of Multi-Modal Spiking Neural Networks Conference 2 2023년도 대한전자공학회 하계종합학술대회 2023년도 대한전자공학회 하계종합학술대회 KO 제주도 2023-06-28 2023년도 대한전자공학회 하계학술대회 논문집