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TextFormer: A Query-based End-to-end Text Spotter with mixed supervision

Machine Intelligence Research 2024年第4期21卷 704-717页

作者： Yukun Zhai Xiaoqiang Zhang Xiameng Qin Sanyuan Zhao Xingping Dong Jianbing Shen School of Computer Science Beijing Institute of TechnologyBeijing 100081China Department of Computer Vision Technology Baidu Inc.Beijing 100193China

End-to-end text spotting is a vital computer vision task that aims to integrate scene text detection and recognition into a unified *** methods heavily rely on region-of-interest(Rol)operations to extract local features and complex post-processing steps to produce final *** address these limitations,we propose TextFormer,a query-based end-to-end text spotter with a transformer ***,using query embedding per text instance,TextFormer builds upon an image encoder and a text decoder to learn a joint semantic understanding for multitask *** allows for mutual training and optimization of classification,segmentation and recognition branches,resulting in deeper feature sharing without sacrificing flexibility or ***,we design an adaptive global aggregation(AGG)module to transfer global features into sequential features for reading arbitrarilyshaped texts,which overcomes the suboptimization problem of Rol ***,potential corpus information is utilized from weak annotations to full labels through mixed supervision,further improving text detection and end-to-end text spotting *** experiments on various bilingual(i.e.,English and Chinese)benchmarks demonstrate the superiority of our *** on the TDA-ReCTS dataset,TextFormer surpasses the state-of-the-art method in terms of 1-NED by 13.2%.

关键词： End-to-end text spotting arbitrarily-shaped texts transformer mixed supervision multitask modeling.

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Research on the relationship between Pension Finance and the Supply-Side Structural Reform in China

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International English Education Research 2017年第1期 45-47页

作者： YANG Zhimin Shanghai University of Engineering Science China

The development of pension finance is of great significance to China. first of all, the development of pension finance is conducive to improving China＇s multi-level and multi-pillar pension system, promote the sustainable development of the social security system; secondly, the development of pension finance will create a new ＂blue ocean＂ in the financial markets, which is conducive to the improvement of China＇s financial system and capital market;finally, the development of pension finance will help supply-side reforms,which is conducive to the healthy development of the national economy of china. But now there are many difficulties： first, the top-design of China＇s social security system is not perfect; secondly, the current development model of pension finance in China is unclear, the return on investment mechanism is not perfect, the attractiveness of these projects needs to be improved; finally, under the background of Interact finance, mixed supervision is imminent. Therefore, under the new economic conditions must be structured from the supply side of the reform, the development of pension funds to seek the right ideas.

关键词： pension finance return on investment mechanism mixed supervision supply-side structural reform

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A Metal Surface Defect Detection Algorithm Based on mixed Supervised and Cross Stage Partial Darknet

A Metal Surface Defect Detection Algorithm Based on Mixed Su...

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第43届中国控制会议

作者： Ronghua Zong Qingjie Liu Jie Wang Xinming Jia Na Qin Deqing Huang School of Electrical Engineering Southwest Jiaotong University Chengdu Aircraft Industry (Group) Co. Ltd

In response to the limitations of traditional visual identification detection methods,such as low accuracy of metal structure surface damage detection and high dependence on labeled data,a mixed supervised model based on cross stage partial(CSP) Darknet is *** utilizing the CSPDarkNet for feature extraction,the capability of model feature extraction is enhanced while meeting lightweight ***,the architecture introduces a feature pyramid structure to fuse different scale feature layers in order to strengthen network representation ***,a non-local attention mechanism is employed to enhance the contextual modeling ability in image ***,the use of a mixed supervised training approach is explored,and the impact of pixel-level label proportions on detection accuracy is *** a result,high accuracy is achieved in the industrial inspection datasets KolektorSDD,meeting practical requirements.

关键词： Defect detection mixed supervision Feature pyramid networks Non-local attention mechanism

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