Framework based on parameterized images on ResNet to identify intrusions in smartwatches or other related devices


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<meta name="Description" CONTENT="Artificial Intelligence Journal" />
<meta name="r0identifier" content="b67b54ef535ceeaf4b3bf38c0cdf8c0b" />
RxRegistration ID
R0Hash MD5 (of R3):b67b54ef535ceeaf4b3bf38c0cdf8c0b
R1Registration number (in the domain editorialia.com at WordPress):dmeditorialiawp.30621
R2Date-p-order (ddmmyyyypx): 29082021p1
R3Cid (combined id R1+R2):dmeditorialiawp.3062129082021p1
R4Resource official title:Framework based on parameterized images on ResNet to identify intrusions in smartwatches or other related devices
R5Publisher:The Bible of AI ™ OpenScience
R6Resource website (1) ( #OpenAccess | #Openscience ): https://www.openscience.online/pub/framework-based-on-parameterized-images-on-resnet-to-identify-intrusions-in-smartwatches-or-other-related-devices/release/1
R9DOI:10.21428/36973002.c76458f1
R12Authors (separated by commas):Lloret Egea, J. A., Medina Lloret, C., Hernández González, A., Díaz Raboso, D., Campos, C., Riveros Guzmán, K., … Terrés Lloret, H. M. (2021)
R14Keyword (selected 1 among the labels applied to this entry):=cybersecurity
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R17Digital signature URL:Pending signature

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