Cargando…
Suspicious Behavior Detection with Temporal Feature Extraction and Time-Series Classification for Shoplifting Crime Prevention
The rise in crime rates in many parts of the world, coupled with advancements in computer vision, has increased the need for automated crime detection services. To address this issue, we propose a new approach for detecting suspicious behavior as a means of preventing shoplifting. Existing methods a...
Autores principales: | Nazir, Amril, Mitra, Rohan, Sulieman, Hana, Kamalov, Firuz |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10347130/ https://www.ncbi.nlm.nih.gov/pubmed/37447661 http://dx.doi.org/10.3390/s23135811 |
Ejemplares similares
-
Shoplifting
por: Baird, Josephine
Publicado: (1963) -
Nested ensemble selection: An effective hybrid feature selection method
por: Kamalov, Firuz, et al.
Publicado: (2023) -
Machine learning based approach to exam cheating detection
por: Kamalov, Firuz, et al.
Publicado: (2021) -
The Influence of Alcohol Consumption on Fighting, Shoplifting and Vandalism in Young Adults
por: Evans, Ieuan, et al.
Publicado: (2021) -
Using Social Signals to Predict Shoplifting: A Transparent Approach to a Sensitive Activity Analysis Problem
por: Reid, Shane, et al.
Publicado: (2021)