{"title":"通过磁性材料中的物理存储计算进行视频识别","authors":"Kaito Kobayashi, Y. Motome","doi":"10.3938/npsm.73.1155","DOIUrl":null,"url":null,"abstract":"Nonlinear spin dynamics in magnetic materials offers a promising avenue for implementing physical reservoir computing, one of the most accomplished brain-inspired frameworks for information processing. In this study, we investigate the practical utility of magnetic physical reservoirs by assessing their performance in a video recognition task. Leveraging a recently developed spatiotemporal parallelization scheme, our reservoir achieves accurate classifications of previously provided images. Our findings pave the way for the development of visual sensors based on the magnetic physical reservoir computing.","PeriodicalId":19186,"journal":{"name":"New Physics: Sae Mulli","volume":"23 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Video Recognition by Physical Reservoir Computing in Magnetic Materials\",\"authors\":\"Kaito Kobayashi, Y. Motome\",\"doi\":\"10.3938/npsm.73.1155\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nonlinear spin dynamics in magnetic materials offers a promising avenue for implementing physical reservoir computing, one of the most accomplished brain-inspired frameworks for information processing. In this study, we investigate the practical utility of magnetic physical reservoirs by assessing their performance in a video recognition task. Leveraging a recently developed spatiotemporal parallelization scheme, our reservoir achieves accurate classifications of previously provided images. Our findings pave the way for the development of visual sensors based on the magnetic physical reservoir computing.\",\"PeriodicalId\":19186,\"journal\":{\"name\":\"New Physics: Sae Mulli\",\"volume\":\"23 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"New Physics: Sae Mulli\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3938/npsm.73.1155\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Physics and Astronomy\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"New Physics: Sae Mulli","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3938/npsm.73.1155","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Physics and Astronomy","Score":null,"Total":0}
Video Recognition by Physical Reservoir Computing in Magnetic Materials
Nonlinear spin dynamics in magnetic materials offers a promising avenue for implementing physical reservoir computing, one of the most accomplished brain-inspired frameworks for information processing. In this study, we investigate the practical utility of magnetic physical reservoirs by assessing their performance in a video recognition task. Leveraging a recently developed spatiotemporal parallelization scheme, our reservoir achieves accurate classifications of previously provided images. Our findings pave the way for the development of visual sensors based on the magnetic physical reservoir computing.
期刊介绍:
New Physics: Sae Mulli monthly publishes peer-reviewed research papers and review papers which make significant, original and correct contributions to one of four categories of physics: 1) review of current physics topics, 2) applied physics(condensed matter, optics, etc.), 3) particle and nuclear physics, 4) other areas of physics (physics education, atomic and molecular physics, interdisciplinary, etc.). Both experimental and theoretical papers are accepted. Papers should be written in Korean or English. The review papers deliver the current physics topics of interests and the current instrumentation (both experimental and theoretical) knowledge at the university level so that even advanced high school students or undergraduate students can access easily. Papers based on successful and original student projects done at Korean local universities are specially welcome.