DC Field | Value | Language |
---|---|---|
dc.contributor.author | Song, Hanchan | ko |
dc.contributor.author | Lee, Min Gu | ko |
dc.contributor.author | Kim, Gwangmin | ko |
dc.contributor.author | Kim, Do Hoon | ko |
dc.contributor.author | Kim, Geunyoung | ko |
dc.contributor.author | Park, Woojoon | ko |
dc.contributor.author | Rhee, Hakseung | ko |
dc.contributor.author | In, Jae Hyun | ko |
dc.contributor.author | Kim, Kyung Min | ko |
dc.date.accessioned | 2024-09-05T04:00:05Z | - |
dc.date.available | 2024-09-05T04:00:05Z | - |
dc.date.created | 2024-08-29 | - |
dc.date.created | 2024-08-29 | - |
dc.date.issued | 2024-05 | - |
dc.identifier.citation | ADVANCED MATERIALS, v.36, no.18 | - |
dc.identifier.issn | 0935-9648 | - |
dc.identifier.uri | http://hdl.handle.net/10203/322630 | - |
dc.description.abstract | Insects can efficiently perform object motion detection via a specialized neural circuit, called an elementary motion detector (EMD). In contrast, conventional machine vision systems require significant computational resources for dynamic motion processing. Here, a fully memristive EMD (M-EMD) is presented that implements the Hassenstein-Reichardt (HR) correlator, a biological model of the EMD. The M-EMD consists of a simple Wye (Y) configuration, including a static resistor, a dynamic memristor, and a Mott memristor. The resistor and dynamic memristor introduce different signal delays, enabling spatio-temporal signal integration in the subsequent Mott memristor, resulting in a direction-selective response. In addition, a neuromorphic system is developed employing the M-EMDs to predict a lane-changing maneuver by vehicles on the road. The system achieved a high accuracy (> 87%) in predicting future lane-changing maneuvers on the Next Generation Simulation (NGSIM) dataset while reducing the computational cost by 92.9% compared to the conventional neuromorphic system without the M-EMD, suggesting its strong potential for edge-level computing. | - |
dc.language | English | - |
dc.publisher | WILEY-V C H VERLAG GMBH | - |
dc.title | Fully Memristive Elementary Motion Detectors for a Maneuver Prediction | - |
dc.type | Article | - |
dc.identifier.wosid | 001152529300001 | - |
dc.identifier.scopusid | 2-s2.0-85183441571 | - |
dc.type.rims | ART | - |
dc.citation.volume | 36 | - |
dc.citation.issue | 18 | - |
dc.citation.publicationname | ADVANCED MATERIALS | - |
dc.identifier.doi | 10.1002/adma.202309708 | - |
dc.contributor.localauthor | Kim, Kyung Min | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | maneuver predictions | - |
dc.subject.keywordAuthor | memristors | - |
dc.subject.keywordAuthor | motion detections | - |
dc.subject.keywordAuthor | neuromorphic visions | - |
dc.subject.keywordAuthor | Hassenstein-Reichardt model | - |
dc.subject.keywordPlus | MOTT MEMRISTORS | - |
dc.subject.keywordPlus | DYNAMICS | - |
dc.subject.keywordPlus | SENSOR | - |
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