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A Crowdsourcing Semi-Supervised LSTM Training Approach to Identify Novel Items in Emerging Artificial Intelligent Environments

Serra, Edoardo
•
Akella, Haritha
•
Cuzzocrea, Alfredo
2019
  • conference object

Abstract
Applying Deep Learning Techniques to CAN Bus Attacks for Supporting Identification and Analysis Tasks
DOI
10.1109/ICMLA.2018.00241
WOS
WOS:000463034400233
Archivio
http://hdl.handle.net/11368/2939100
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85062206404
https://ieeexplore.ieee.org/document/8614266
Diritti
closed access
license:copyright editore
FVG url
https://arts.units.it/request-item?handle=11368/2939100
Soggetti
  • Deep learning

  • LSTM

  • Novelty detection

  • Recurrent Neural Netw...

  • Semi unsuperevised

  • Artificial Intelligen...

  • Computer Networks and...

  • Computer Science Appl...

  • 1707

  • Safety, Risk, Reliabi...

  • Signal Processing

  • Decision Sciences (mi...

Web of Science© citazioni
2
Data di acquisizione
Mar 7, 2024
Visualizzazioni
1
Data di acquisizione
Apr 19, 2024
Vedi dettagli
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