Multistrengthening Module-Based Salient Object Detection

作者：Qian Zhao, Haifeng Wang, Junpeng Dang, Songlin Li, Rong‐Chi Chang, Yanbin Fang, Zhi Zhang, Jie Peng, Yang Yang · 发表于：Mathematical Problems in Engineering · 年份：2021 · DOI：10.1155/2021/2472676 · 被引用次数：1 · 研究领域：Visual Attention and Saliency Detection、Advanced Neural Network Applications、Advanced Image and Video Retrieval Techniques

Object detection is a classical research problem in computer vision, and it is widely used in the automatic monitoring field of various production safety. However, current object detection techniques often suffer low detection accuracy when an image has a complex background. To solve this problem, this paper proposes a double U-shaped multireinforced unit structure network (DUMRN). The proposed network consists of a detection module (DM), a reinforced module (RM), and a salient loss function (SLF). Extensive experiments on five public datasets and a practical application dataset are conducted and compared against nine state-of-the-art methods. The experiment results show the superiority of our method over the state of the art.