XueYing Lin - IEEE Xplore Author Profile

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An improved YOLO v4 with lightweight parameters was proposed to detect strawberry flowers in real-time. The improvement was accomplished through two strategies. Firstly, the backbone network was lightweight designed by replacing standard convolution with grouped convolution, under the Visual Geometry Group (VGG) and re-parameterization VGG (Rep-VGG) frameworks. Secondly, the backbone network was f...Show More
Accurate and efficient detection for target crops is crucial to develop intelligent agriculture. A great deal of studies have been devoted to improving the accuracy and efficiency of detection algorithms, but the increasing requirement of computing power makes them particularly difficult to implement on embedded devices. Although some methods have been proposed to accelerate inference by lightenin...Show More
Salient object detection is a fundamental computer vision task. The majority of current algorithms focus on the use of edge information. However, these algorithms are limited to one-way auxiliary training or feature fusion to improve salient features. In this paper, we propose a novel framework for salient object detection, called Bi-Directional Selectivity Refinement Network (BSRN). Our framework...Show More