Results 211 to 220 of about 114,773 (269)

VisualRNet: Lightweight Camera Rotation Estimation from Low-Resolution Optical Flow via Cross-Modal Supervision. [PDF]

Sensors (Basel)
Yang X, Wang H, Ni J.
europepmc   +1 more source

Robust and Lightweight Federated Learning for NB-IoT Security: A Blockchain-Verified CNN-RNN Approach. [PDF]

Sensors (Basel)
Özmen G, Yiltas-Kaplan D.
europepmc   +1 more source

Development and validation of a blinding eye disease screening system based on lightweight convolutional neural networks: A diagnostic accuracy study. [PDF]

Medicine (Baltimore)
Gong R, Zheng H, Lang Z, Xu B, Jia W.
europepmc   +1 more source

A Lightweight Hybrid Authentication and Key Agreement Protocol for Decentralized Device-to-Device Communication with Post-Quantum Confidentiality. [PDF]

Sensors (Basel)
Savón-Berenguer A, Moraru SA, García-Naranjo JC, Braeken A.   +3 more
europepmc   +1 more source

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Nothing Lightweight About Lightweighting

Machinery, 2021
The shift to lightweighting across manufacturing sectors is presenting benefits and challenges to machining shops. Justin Burns investigates
openaire   +1 more source

Lightweight family polymorphism

Journal of Functional Programming, 2005
Abstract Family polymorphism has been proposed for object-oriented languages as a solution to supporting reusable yet type-safe mutually recursive classes. A key idea of family polymorphism is the notion of families, which are used to group mutually recursive classes.
Atsushi Igarashi, Chieri Saito, Mirko Viroli   +2 more
openaire   +3 more sources

Lightweight steganography on smartphones

CCNC 2006. 2006 3rd IEEE Consumer Communications and Networking Conference, 2006., 2006
Steganography is an historical technique to send secret messages embedded into carrier messages. The intro- duction of computers provided very sophisticated techniques to create carrier messages, to embed the secret, and to detect steganographic messages.
AMOROSO, ALESSANDRO, M. Masotti
openaire   +2 more sources

Lightweight Parsing of Classifications into Lightweight Ontologies

2010
Understanding metadata written in natural language is a premise to successful automated integration of large scale, language-rich, classifications such as the ones used in digital libraries. We analyze the natural language labels within classification by exploring their syntactic structure, we then show how this structure can be used to detect patterns
Aliaksandr Autayeu, Fausto Giunchiglia, Pierre Andrews   +2 more
openaire   +1 more source