Results 311 to 320 of about 4,197,782 (360)
Some of the next articles are maybe not open access.
DeepFace: Closing the Gap to Human-Level Performance in Face Verification
2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014In modern face recognition, the conventional pipeline consists of four stages: detect => align => represent => classify. We revisit both the alignment step and the representation step by employing explicit 3D face modeling in order to apply a piecewise ...
Yaniv Taigman +3 more
semanticscholar +1 more source
Verification Is Experimentation!
International Journal on Software Tools for Technology Transfer, 2000zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +3 more sources
AJN, American Journal of Nursing, 2017
A visiting nurse finds himself cast as a player in a universal drama.
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A visiting nurse finds himself cast as a player in a universal drama.
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Blockchain-based Mobility Verification of Connected Cars
Consumer Communications and Networking Conference, 2020Several applications for connected cars leverage the mobility information periodically broadcasted by cars through standard vehicle-to-vehicle messages.
Carla-Fabiana Chiasserini +4 more
semanticscholar +1 more source
ACM SIGLOG News, 2018
This quarter we have an expert introduction and survey about verification motivated problems on weighted automata, with max-plus and cost register models in focus. Starting gently, and by means of examples, we are quickly led to the state of the art.
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This quarter we have an expert introduction and survey about verification motivated problems on weighted automata, with max-plus and cost register models in focus. Starting gently, and by means of examples, we are quickly led to the state of the art.
openaire +2 more sources
SIAM Journal on Computing, 2000
Summary: We provide an \(O(n^2 \log{1 \over \delta})\) time randomized algorithm to check whether a given operation \(\circ :S \times S \rightarrow S\) is associative (where \(n=|S|\) and \(\delta>0\) is the error probability required of the algorithm).
Sridhar Rajagopalan, Leonard J. Schulman
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Summary: We provide an \(O(n^2 \log{1 \over \delta})\) time randomized algorithm to check whether a given operation \(\circ :S \times S \rightarrow S\) is associative (where \(n=|S|\) and \(\delta>0\) is the error probability required of the algorithm).
Sridhar Rajagopalan, Leonard J. Schulman
openaire +3 more sources
MobileFaceNets: Efficient CNNs for Accurate Real-time Face Verification on Mobile Devices
Chinese Conference on Biometric Recognition, 2018We present a class of extremely efficient CNN models, MobileFaceNets, which use less than 1 million parameters and are specifically tailored for high-accuracy real-time face verification on mobile and embedded devices.
Sheng Chen +3 more
semanticscholar +1 more source