Automated detection and counting of Artemia using U-shaped fully convolutional networks and deep convolutional networks
作者：
Highlights：
• Automated Artemia detection is challenging and has so far never been addressed.
• A marker proposal network using U-shaped fully convolutional networks is designed.
• The marker proposal network can separate adjacent objects and obtain candidates.
• A target classifier using deep convolutional networks is built.
• The proposed method can accurately detect Artemia objects in images.
摘要
•Automated Artemia detection is challenging and has so far never been addressed.•A marker proposal network using U-shaped fully convolutional networks is designed.•The marker proposal network can separate adjacent objects and obtain candidates.•A target classifier using deep convolutional networks is built.•The proposed method can accurately detect Artemia objects in images.
论文关键词：Object detection,Target classification,Artemia detection and counting,Marker proposal network,U-shaped fully convolutional network,Deep convolutional network
论文评审过程：Received 20 September 2019, Revised 30 November 2020, Accepted 31 December 2020, Available online 7 January 2021, Version of Record 30 January 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.114562
