Cargando…
An Extended Review Concerning the Relevance of Deep Learning and Privacy Techniques for Data-Driven Soft Sensors
The continuously increasing number of mobile devices actively being used in the world amounted to approximately 6.8 billion by 2022. Consequently, this implies a substantial increase in the amount of personal data collected, transported, processed, and stored. The authors of this paper designed and...
Autores principales: | Bocu, Razvan, Bocu, Dorin, Iavich, Maksim |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824402/ https://www.ncbi.nlm.nih.gov/pubmed/36616892 http://dx.doi.org/10.3390/s23010294 |
Ejemplares similares
-
Relevant Cybersecurity Aspects of IoT Microservices Architectures Deployed over Next-Generation Mobile Networks
por: Aldea, Constantin Lucian, et al.
Publicado: (2022) -
Spontaneous Intestinal Perforation: An Atypical Presentation of Neutropenic Enterocolitis—A Case Report
por: Canbolat Ayhan, Aylin, et al.
Publicado: (2014) -
Industrial Semi-Supervised Dynamic Soft-Sensor Modeling Approach Based on Deep Relevant Representation Learning
por: Moreira de Lima, Jean Mário, et al.
Publicado: (2021) -
Medical imaging deep learning with differential privacy
por: Ziller, Alexander, et al.
Publicado: (2021) -
Analysis of Application Examples of Differential Privacy in Deep Learning
por: Shen, Zhidong, et al.
Publicado: (2021)