Postures anomaly tracking and prediction learning model over crowd data analytics.

Aljuaid, Hanan; Akhter, Israr; Alsufyani, Nawal; Shorfuzzaman, Mohammad; Alarfaj, Mohammed; Alnowaiser, Khaled; Jalal, Ahmad; Park, Jeongmin

Aljuaid, Hanan; Akhter, Israr; Alsufyani, Nawal; Shorfuzzaman, Mohammad; Alarfaj, Mohammed; Alnowaiser, Khaled; Jalal, Ahmad; Park, Jeongmin.

Aljuaid H; Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia.
Akhter I; Department of Computer Science, Bahria University, Islamabad, Pakistan.
Alsufyani N; Department of Computer Science, Taif University, Taif, Saudi Arabia.
Shorfuzzaman M; Department of Computer Science, Taif University, Taif, Saudi Arabia.
Alarfaj M; Department of Electrical Engineering, King Faisal University, Al-Ahsa, Saudi Arabia.
Alnowaiser K; Department of Computer Engineering, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia.
Jalal A; Department of Computer Science, Air University, Islamabad, Pakistan.
Park J; Department of Computer Engineering, Tech University of Korea, Sangidaehak-ro, Siheung-si, South Korea.

PeerJ Comput Sci ; 9: e1355, 2023.

Article en En | MEDLINE | ID: mdl-37346503

Palabras clave

Anomaly detection; Compressive tracking Algorithm; Crowd based data; Data optimization; E-Learning; Fused dense optical flow; Fuzzy C mean; Gradient patches; Predication model; T-distributed stochastic neighbor embedding

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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Año: 2023 Tipo del documento: Article

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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Año: 2023 Tipo del documento: Article