Cargando…
Applications of Shaped-Charge Learning
It is well known that deep learning (DNN) has strong limitations due to a lack of explainability and weak defense against possible adversarial attacks. These attacks would be a concern for autonomous teams producing a state of high entropy for the team’s structure. In our first article for this Spec...
Autor principal: | Galitsky, Boris |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10670459/ https://www.ncbi.nlm.nih.gov/pubmed/37998188 http://dx.doi.org/10.3390/e25111496 |
Ejemplares similares
-
Shaped-Charge Learning Architecture for the Human–Machine Teams
por: Galitsky, Boris, et al.
Publicado: (2023) -
Developing enterprise chatbots: learning linguistic structures
por: Galitsky, Boris
Publicado: (2019) -
La mécanique quantique: problèmes résolus
por: Galitsky, Victor M, et al.
Publicado: (2002) -
Application of PTFE/Al Reactive Materials for Double-Layered Liner Shaped Charge
por: Wang, Haifu, et al.
Publicado: (2019) -
Research on the Formation Characteristics of the Shaped Charge Jet from the Shaped Charge with a Trapezoid Cross-Section
por: Ma, Bin, et al.
Publicado: (2022)