In recent years, aquaculture industry in China is developing rapidly, and especially, China has the largest aquaculture area and the most output in the world. In the past, traditional aquaculture mainly depended on ma...In recent years, aquaculture industry in China is developing rapidly, and especially, China has the largest aquaculture area and the most output in the world. In the past, traditional aquaculture mainly depended on manual labour to breed and gain aquatic organisms. However, with the increasing scale of production and the continuous improvement of science and technology, the traditional aquaculture approach has become more and more unsuitable for the development of the times. With the rapid development of computer technology, computer vision technology infiltrates through the traditional aquaculture industry quickly and improves the aquaculture production efficiency .This paper mainly introduces the basic situation of computer vision technology and summarizes the application of computer vision technology in aquaculture industry at home and abroad. The paper concludes with the expectation of application of computer vision in the aquaculture.展开更多
Salient detection approaches mainly use single local cues or global cues as its inputs features to detect salient objects,which are sensitive to complex background,so the effect of detection were not satisfactory.In t...Salient detection approaches mainly use single local cues or global cues as its inputs features to detect salient objects,which are sensitive to complex background,so the effect of detection were not satisfactory.In this paper,we investigate the traits of saliency detection and observed the two following facts:Firstly,high-level saliency cues achieve better saliency detection results than low-level saliency cues.Secondly,multi-difference cues achieve better saliency detection results than single difference cues.Based on deeply analysis,we proposed an image saliency detection algorithm through high level multi-difference cues(HMDS).By using multi-difference,not only HMDS could remove the non-salient region effectively,but also it could enhance the pixel value of salient region at the same time.In order to evaluate the performance of HMDS,the proposed method is compared with seven state-of-the-art algorithms on five popular datasets.The final experimental results show that the proposed method performs effectiveness,and will have a perfect application prospect.展开更多
文摘In recent years, aquaculture industry in China is developing rapidly, and especially, China has the largest aquaculture area and the most output in the world. In the past, traditional aquaculture mainly depended on manual labour to breed and gain aquatic organisms. However, with the increasing scale of production and the continuous improvement of science and technology, the traditional aquaculture approach has become more and more unsuitable for the development of the times. With the rapid development of computer technology, computer vision technology infiltrates through the traditional aquaculture industry quickly and improves the aquaculture production efficiency .This paper mainly introduces the basic situation of computer vision technology and summarizes the application of computer vision technology in aquaculture industry at home and abroad. The paper concludes with the expectation of application of computer vision in the aquaculture.
文摘Salient detection approaches mainly use single local cues or global cues as its inputs features to detect salient objects,which are sensitive to complex background,so the effect of detection were not satisfactory.In this paper,we investigate the traits of saliency detection and observed the two following facts:Firstly,high-level saliency cues achieve better saliency detection results than low-level saliency cues.Secondly,multi-difference cues achieve better saliency detection results than single difference cues.Based on deeply analysis,we proposed an image saliency detection algorithm through high level multi-difference cues(HMDS).By using multi-difference,not only HMDS could remove the non-salient region effectively,but also it could enhance the pixel value of salient region at the same time.In order to evaluate the performance of HMDS,the proposed method is compared with seven state-of-the-art algorithms on five popular datasets.The final experimental results show that the proposed method performs effectiveness,and will have a perfect application prospect.
