Multi-Scale Vehicle Detection for Foreground-Background Class Imbalance with Improved YOLOv2.

Wu, Zhongyuan; Sang, Jun; Zhang, Qian; Xiang, Hong; Cai, Bin; Xia, Xiaofeng

Wu, Zhongyuan; Sang, Jun; Zhang, Qian; Xiang, Hong; Cai, Bin; Xia, Xiaofeng.

Afiliação

Wu Z; Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education, Chongqing University, Chongqing 40004, China.
Sang J; School of Big Data & Software Engineering, Chongqing University, Chongqing 401331, China.
Zhang Q; Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education, Chongqing University, Chongqing 40004, China. jsang@cqu.edu.cn.
Xiang H; School of Big Data & Software Engineering, Chongqing University, Chongqing 401331, China. jsang@cqu.edu.cn.
Cai B; Key Laboratory of Dependable Service Computing in Cyber Physical Society of Ministry of Education, Chongqing University, Chongqing 40004, China.
Xia X; School of Big Data & Software Engineering, Chongqing University, Chongqing 401331, China.

Sensors (Basel) ; 19(15)2019 Jul 30.

Article em En | MEDLINE | ID: mdl-31366022

Palavras-chave

YOLOv2; anchor box; focal loss; multi-scale; vehicle detection

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2019 Tipo de documento: Article País de afiliação: China

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