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Microstructure recognition of steels by machine learning based on visual attention mechanism

Journal of Iron and Steel Research International 2024年第4期31卷 909-923页

作者： Xing-yu Chen Lin Cheng Cheng-yang Hu Yu-peng Zhang Kai-ming Wu The State Key Laboratory of Refractories and Metallurgy Hubei Province Key Laboratory of Systems Science on Metallurgical ProcessingInternational Research Institute for Steel TechnologyCollaborative Center on Advanced SteelsWuhan University of Science and TechnologyWuhan 430081HubeiChina Metals Valley and Band(Foshan)Metallic Composite Materials Co. Ltd.Foshan 528000GuangdongChina

U-Net has achieved good performance with the small-scale datasets through skip connections to merge the features of the low-level layers and high-level layers and has been widely utilized in biomedical image segmentation as well as recent microstructure image segregation of the *** representative visual attention mechanism modules,named as squeeze-and-excitation networks,convolutional block attention module,and extended calibration algorithm,were intro-duced into the traditional U-Net architecture to further improve the prediction *** is found that compared with the original U-Net architecture,the evaluation index of the improved U-Net architecture has been significantly improved for the microstructure segmentation of the steels with the ferrite/martensite composite microstructure and pearlite/ferrite composite microstructure and the complex martensite/austenite island/bainite microstructure,which demonstrates the advantages of the utilization of the visual attention mechanism in the microstructure *** reasons for the accuracy improvement were discussed based on the feature maps analysis.

关键词： Microstructure recognition-Steel Machine learning visual attention mechanism visualization

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A Novel Method for Infrared Object Detection Based on Human visual attention mechanism

A Novel Method for Infrared Object Detection Based on Human ...

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第14届中国系统仿真技术及其应用学术年会

作者： Mingqing ZHU 1,Tong GAN 1,Zonghai CHEN 2 1 China Electronics Technology Group Corporation No.38 Research Institute,Hefei,China 2 Department of Automation of University of Science and Technology of China,Hefei,China

Local visual attention mechanism （LVAM） is firstly presented and combined with bottom-up visual attention mechanism （VAM） to form a unified visual attention framework,based on which a novel infrared object detection method is *** feature is applied to build visual saliency *** Shannon entropy density is used to determine the position of visual attention *** object area is extracted with region growing technique imitating local *** demonstrate the outperformance of our proposed visual attention framework and infrared object detection method.

关键词： Infrared object detection visual attention mechanism visual saliency map region growing

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Paper Defects Detection via visual attention mechanism

Paper Defects Detection via Visual Attention Mechanism

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第三十届中国控制会议

作者： JIANG Ping~1,GAO Tao~(2,3) 1.School of Control Science & Engineering,University of Jinan,Jinan 250022,P.R.China 2.Electronic Information Products Supervision and Inspection Institute of Hebei Province,Shijiazhuang 050071,Hebei,P.R.China 3.Industry and Information Technology Department of Hebei Province,Shijiazhuang 050051,Hebei,P.R.China

＜正＞An improved paper defects detection method based on visual attention mechanism computation model is ***,multi-scale feature maps are extracted by linear ***,the comparative maps are obtained by carrying out center-surround difference ***,the saliency map is obtained by combining the conspicuity maps, which is gained by combining the multi-scale comparative ***,the seed point of watershed segmentation is determined by competition among salient points in the saliency map and the defect regions are segmented from the *** results show the efficiency of the approach for paper defects detection.

关键词： Defect Detection visual attention mechanism Saliency Map Watershed Segmentation

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Research of Human visual Perception mechanisms for Object Tracking

Research of Human Visual Perception Mechanisms for Object Tr...

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第13届中国系统仿真技术及其应用学术年会

作者：赵宇宙陈宗海 Department of Automation University of Science and Technology of China

The theories and models of human visual perception are aim to understand and emulate the intelligent properties of human vision system,and have important reference value to traditional computer vision research. In this paper,based on mechanisms of visual attention,we discuss the problem of object tracking in the perspective of visual attention. A framework of attention based tracking strategy is proposed and implemented,and the advantages and lacks are discussed after experiments. We hope to provide a reference for the further research of biologically motivated object tracking.

关键词： visual perception visual attention mechanism object tracking feature selection feature learning

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