JP2023554336A5 - - Google Patents

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JP2023554336A5
JP2023554336A5 JP2023535704A JP2023535704A JP2023554336A5 JP 2023554336 A5 JP2023554336 A5 JP 2023554336A5 JP 2023535704 A JP2023535704 A JP 2023535704A JP 2023535704 A JP2023535704 A JP 2023535704A JP 2023554336 A5 JP2023554336 A5 JP 2023554336A5
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spatiotemporal
output vector
input data
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JP2023535704A
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JP2023554336A (ja
JP7710520B2 (ja
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JP2023535704A 2020-12-16 2021-12-10 行動バイオメトリクスについての時空間深層学習 Active JP7710520B2 (ja)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US17/123,821 2020-12-16
US17/123,821 US12019720B2 (en) 2020-12-16 2020-12-16 Spatiotemporal deep learning for behavioral biometrics
PCT/IB2021/061560 WO2022130147A1 (en) 2020-12-16 2021-12-10 Spatiotemporal deep learning for behavioral biometrics

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JP2023554336A JP2023554336A (ja) 2023-12-27
JP2023554336A5 true JP2023554336A5 (https=) 2024-01-12
JP7710520B2 JP7710520B2 (ja) 2025-07-18

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US (1) US12019720B2 (https=)
JP (1) JP7710520B2 (https=)
CN (1) CN116508028B (https=)
DE (1) DE112021006507T5 (https=)
GB (1) GB2617940B (https=)
WO (1) WO2022130147A1 (https=)

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CN119851343A (zh) * 2024-12-18 2025-04-18 南京邮电大学 一种基于视频步态的疲劳检测方法

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