Identification algorithm of fishing vessel operation type based on Feature Fusion

Gao, Bingtao; Wang, Lei; Zhai, Zhengang; Wang, Yinjie; Zhu, Yunya; Yao, Tengjun; Liú, Dan; Zhang, Li

doi:10.1109/icaiis49377.2020.9194842

Cited by 1 publication

(1 citation statement)

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“…Many scholars have studied the fishing behavior through the fishing vessel operation data of VMS system, and achieved good results. For example, Gao et al [37] proposed a feature fusion recognition algorithm to transform the fishing vessel operation type identification problem into a multi-classification problem based on feature fusion. By extracting the feature information of VMS data, the feature fusion space of the target task was constructed, and the fishing vessel operation-type recognition model was established.…”

Section: Identifying Behavioral Characteristics Of Fishing Vesselsmentioning

confidence: 99%

Application of Artificial Intelligence in the Study of Fishing Vessel Behavior

Cheng,

Zhang,

Chen

et al. 2023

Fishes

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Monitoring and understanding the behavior of fishing vessels are important in facilitating effective management, preventing illegal fishing, informing fishing grounds and evaluating effects of harvests on fishery resources. In recent decades, a large quantity of real-time data of fishing vessels have become available with the development of vessel-tracking systems, making it possible to study the behavior of fishing vessels in high spatial and temporal resolutions. To effectively and efficiently deal with the large amount of data, algorithms from artificial intelligence (AI) are increasingly applied in the study of fishing vessel behavior. In this paper, we first introduce the various data sources for studying fishing vessel behavior and compare their pros and cons. Secondly, we review the AI methods that have been used to monitor and extract the behavior of fishing vessels from big data. Then, studies on the physical, ecological and social mechanisms affecting the behavior of fishing vessels were synthesized. Lastly, we review the applications of fishing vessel behavior in fishery science and management.

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Section: Identifying Behavioral Characteristics Of Fishing Vesselsmentioning

confidence: 99%