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https://hdl.handle.net/10356/138149
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DC Field | Value | Language |
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dc.contributor.author | Wan, Changjin | en_US |
dc.contributor.author | Cai, Pingqiang | en_US |
dc.contributor.author | Wang, Ming | en_US |
dc.contributor.author | Qian, Yan | en_US |
dc.contributor.author | Huang, Wei | en_US |
dc.contributor.author | Chen, Xiaodong | en_US |
dc.date.accessioned | 2020-04-27T03:07:29Z | - |
dc.date.available | 2020-04-27T03:07:29Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Wan, C., Cai, P., Wang, M., Qian, Y., Huang, W., & Chen, X. (2020). Artificial Sensory Memory. Advanced Materials, 32(15), 1902434-. doi:10.1002/adma.201902434 | en_US |
dc.identifier.issn | 0935-9648 | en_US |
dc.identifier.uri | https://hdl.handle.net/10356/138149 | - |
dc.description.abstract | Sensory memory, formed at the beginning while perceiving and interacting with the environment, is considered a primary source of intelligence. Transferring such biological concepts into electronic implementation aims at achieving perceptual intelligence, which would profoundly advance a broad spectrum of applications, such as prosthetics, robotics, and cyborg systems. Here, the recent developments in the design and fabrication of artificial sensory memory devices are summarized and their applications in recognition, manipulation, and learning are highlighted. The emergence of such devices benefits from recent progress in both bioinspired sensing and neuromorphic engineering technologies and derives from abundant inspiration and benchmarks from an improved understanding of biological sensory processing. Increasing attention to this area would offer unprecedented opportunities toward new hardware architecture of artificial intelligence, which could extend the capabilities of digital systems with emotional/psychological attributes. Pending challenges are also addressed to aspects such as integration level, energy efficiency, and functionality, which would undoubtedly shed light on the future development of translational implementations. | en_US |
dc.description.sponsorship | NRF (Natl Research Foundation, S’pore) | en_US |
dc.description.sponsorship | ASTAR (Agency for Sci., Tech. and Research, S’pore) | en_US |
dc.description.sponsorship | MOE (Min. of Education, S’pore) | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Advanced Materials | en_US |
dc.rights | This is the peer reviewed version of the following article: Wan, C., Cai, P., Wang, M., Qian, Y., Huang, W., & Chen, X. (2020). Artificial Sensory Memory. Advanced Materials, 32(15), 1902434-, which has been published in final form at http://doi.org/10.1002/adma.201902434. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. | en_US |
dc.subject | Engineering::Materials | en_US |
dc.title | Artificial sensory memory | en_US |
dc.type | Journal Article | en |
dc.contributor.school | School of Materials Science and Engineering | en_US |
dc.contributor.organization | Innovative Center for Flexible Devices | en_US |
dc.contributor.organization | Max Planck – NTU Joint Lab for Artificial Senses | en_US |
dc.identifier.doi | 10.1002/adma.201902434 | - |
dc.description.version | Accepted version | en_US |
dc.identifier.pmid | 31364219 | - |
dc.identifier.scopus | 2-s2.0-85070265618 | - |
dc.identifier.issue | 15 | en_US |
dc.identifier.volume | 32 | en_US |
dc.identifier.spage | 1902434 (1 of 22) | en_US |
dc.identifier.epage | 1902434 (22 of 22) | en_US |
dc.subject.keywords | Artificial Neurons | en_US |
dc.subject.keywords | Bioinspired Sensors | en_US |
item.grantfulltext | open | - |
item.fulltext | With Fulltext | - |
Appears in Collections: | MSE Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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Artificial Sensory Memory.pdf | 6.07 MB | Adobe PDF | View/Open |
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