Results 141 to 150 of about 445 (189)

Bio-mimicking DNA fingerprint profiling for HLS watermarking to counter hardware IP piracy. [PDF]

Sci Rep
Sengupta A, Bhui N, Anshul A, Chourasia V.   +3 more
europepmc   +1 more source

Federated Learning with Assured Privacy and Reputation-Driven Incentives for Internet of Vehicles. [PDF]

Sensors (Basel)
Chai J, Chen M, Zhang W, Wang X, Song J.
europepmc   +1 more source

Classification and Verification of Handwritten Signatures with Time Causal Information Theory Quantifiers. [PDF]

PLoS One, 2016
Rosso OA, Ospina R, Frery AC.
europepmc   +1 more source

Effects of Sleep Duration on Electroencephalographic and Autonomic Nervous System Responses to High-Intensity Exercise. [PDF]

Healthcare (Basel)
Jung JH, So WY, Ko JM.
europepmc   +1 more source

Photonic edge intelligence chip for multi-modal sensing, inference and learning. [PDF]

Nat Commun
Zhang S, Jiang X, Wu B, Zhou H, Xu W, Zhou H, Ruan Z, Dong J, Zhang X.   +8 more
europepmc   +1 more source

ProtoSig: enhancing training data for offline handwritten signature verification using prototypical signatures

Pattern Recognition
Kecia G. de Moura, Robert Sabourin, Rafael M.O. Cruz   +2 more
openaire   +1 more source

Bio-Rollup: a new privacy protection solution for biometrics based on two-layer scalability-focused blockchain. [PDF]

PeerJ Comput Sci
Yun J, Lu Y, Liu X, Guan J.
europepmc   +1 more source

Learning probability distributions of sensory inputs with Monte Carlo predictive coding. [PDF]

PLoS Comput Biol
Oliviers G, Bogacz R, Meulemans A.
europepmc   +1 more source

A Two-Stage Siamese Network Model for Offline Handwritten Signature Verification [PDF]

Symmetry, 2022
Offline handwritten signature verification is one of the most prevalent and prominent biometric methods in many application fields. Siamese neural network, which can extract and compare the writers’ style features, proves to be efficient in verifying the offline signature.
Xiao, Wanghui, Ding, Yuting
exaly   +3 more sources

Features selection for offline handwritten signature verification: state of the art [PDF]

International Journal of Computational Vision and Robotics, 2018
This research comes out with an in-depth review of widely used techniques to handwritten signature verification based, feature selection techniques. The focus of this research is to explore best features selection criteria for signature verification to avoid forgery.
Hoshang Kolivand, Tanzila Saba
exaly   +3 more sources