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Pre-training transformer with dual-branch context content module for table detection in document images
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作者 Yongzhi LI pengle zhang +2 位作者 Meng SUN Jin HUANG Ruhan HE 《虚拟现实与智能硬件(中英文)》 EI 2024年第5期408-420,共13页
Background Document images such as statistical reports and scientific journals are widely used in information technology.Accurate detection of table areas in document images is an essential prerequisite for tasks such... Background Document images such as statistical reports and scientific journals are widely used in information technology.Accurate detection of table areas in document images is an essential prerequisite for tasks such as information extraction.However,because of the diversity in the shapes and sizes of tables,existing table detection methods adapted from general object detection algorithms,have not yet achieved satisfactory results.Incorrect detection results might lead to the loss of critical information.Methods Therefore,we propose a novel end-to-end trainable deep network combined with a self-supervised pretraining transformer for feature extraction to minimize incorrect detections.To better deal with table areas of different shapes and sizes,we added a dual-branch context content attention module(DCCAM)to high-dimensional features to extract context content information,thereby enhancing the network's ability to learn shape features.For feature fusion at different scales,we replaced the original 3×3 convolution with a multilayer residual module,which contains enhanced gradient flow information to improve the feature representation and extraction capability.Results We evaluated our method on public document datasets and compared it with previous methods,which achieved state-of-the-art results in terms of evaluation metrics such as recall and F1-score. 展开更多
关键词 Table detection Document image analysis TRANSFORMER Dilated convolution Deformable convolution Feature fusion
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Scenario-based approach for project portfolio selection in army engineering and manufacturing development 被引量:2
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作者 pengle zhang Kewei Yang +1 位作者 Yajie Dou Jiang Jiang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2016年第1期166-176,共11页
The decisions concerning portfolio selection for army engineering and manufacturing development projects determine the benefit of those projects to the country concerned.Projects are typically selected based on ex ant... The decisions concerning portfolio selection for army engineering and manufacturing development projects determine the benefit of those projects to the country concerned.Projects are typically selected based on ex ante estimates of future return values,which are usually difficult to specify or only generated after project launch.A scenario-based approach is presented here to address the problem of selecting a project portfolio under incomplete scenario information and interdependency constraints.In the first stage,the relevant dominance concepts of scenario analysis are studied to handle the incomplete information.Then,a scenario-based programming approach is proposed to handle the interdependencies to obtain the projects,whose return values are multi-criteria with interval data.Finally,an illustrative example of army engineering and manufacturing development shows the feasibility and advantages of the scenario-based multi-objective programming approach. 展开更多
关键词 scenario-based interdependency group decision making project portfolio selection portfolio decision analysis
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