Deep visual social distancing monitoring to combat COVID-19: A comprehensive survey.

Himeur, Yassine; Al-Maadeed, Somaya; Almaadeed, Noor; Abualsaud, Khalid; Mohamed, Amr; Khattab, Tamer; Elharrouss, Omar

Himeur, Yassine; Al-Maadeed, Somaya; Almaadeed, Noor; Abualsaud, Khalid; Mohamed, Amr; Khattab, Tamer; Elharrouss, Omar.

Afiliación

Himeur Y; Computer Science and Engineering Department, Qatar University, Qatar.
Al-Maadeed S; Computer Science and Engineering Department, Qatar University, Qatar.
Almaadeed N; Computer Science and Engineering Department, Qatar University, Qatar.
Abualsaud K; Computer Science and Engineering Department, Qatar University, Qatar.
Mohamed A; Computer Science and Engineering Department, Qatar University, Qatar.
Khattab T; Electrical Engineering Department, Qatar University, Qatar.
Elharrouss O; Computer Science and Engineering Department, Qatar University, Qatar.

Sustain Cities Soc ; 85: 104064, 2022 Oct.

Article en En | MEDLINE | ID: mdl-35880102

Palabras clave

Bird's eye view; Convolutional neural networks; Euclidean distance; Pedestrian detection; Transfer learning; Visual social distancing monitoring

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sustain Cities Soc Año: 2022 Tipo del documento: Article País de afiliación: Qatar Pais de publicación: Países Bajos

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