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Paper Defects Recognition Based on Deformable Convolution

Palpu Chongi Gisul/Journal of Korea Technical Association of the Pulp and Paper Industry 2022年第2期54卷 37-50页

作者： Qu, Yun-Hui Tang, Wei Feng, Bo Computer Teaching and Research Section Xi’an Medical University China Department of Electric and Control Engineering Shaanxi University of Science & Technology China

There are some problems in traditional paper defects classification, such as the poor generalization performance, less types of recognition, and insufficient recognition accuracy. The deep learning method provides a new scheme for paper defects classification. However, convolutional neural network has strict requirements for the size of the input image. This requires that in the process of practical engineering application, for the collected paper defect images to be classified, the area containing paper defect must be segmented during preprocessing, and then the size of the paper defect area must be adjusted to meet the input requirements of the adopted classifier. To solve the above problems, the two-stage target detection network Faster R-CNN (Region-Convolutional Neural Network) was used in paper defects recognition to solve the problem of the size requirements of the input image;In addition, the deformable convolution layer was added after the traditional convolution layer to learn the characteristics of paper defects more efficiently and accurately, so as to improve the accuracy and accuracy of paper defects recognition and classification;Finally, the deformable RoI (Region-of-Interest) pooling layer was used to replace the RoI pooling layer of classic Faster R-CNN to locate and classify the paper defects area more accurately. Experiments show that the proposed algorithm has a further improvement in accuracy and scalability compared with the previous algorithm. © 2022 Korean Technical Assoc. of the Pulp and Paper Industry. All rights reserved.

关键词： Convolution

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Adaptive Compression-Encryption Scheme for Medical Image Based on Improved Compressive Sensing and Deoxyribonucleic Acid Coding-Compression

Adaptive Compression-Encryption Scheme for Medical Image Bas...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Xue, Xianglian Jin, Haiyan Zhou, Changjun Xi'an University of Technology School of Computer Science and Engineering Xi'an China Shaanxi University of Chinese Medicine Section of Computer Teaching and Research Xianyang China Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China Zhejiang Normal University School of Computer Science and Technology Jinhua China

ISBN: (纸本)9798350386226

Medical images often occupy large storage space and contain patient privacy or sensitive information, which makes them difficult and unsafe to be transmitted through the network. This paper proposed an adaptive compression-encryption scheme based on improved compressive sensing (CS) and deoxyribonucleic acid (DNA) coding-compression, which helps to solve the above problem. In the proposed scheme, first the original medical image was compressed to a floating point CS matrix using the discrete wavelet transform and the partial Hadamard matrix. The CS matrix was then normalized and rounded for matrix quantification. The result of quantification was fed to DNA fixed encoding and DNA run length coding for encryption and secondary compression. Finally the compressed-encrypted image was obtained after DNA dynamic encoding-decoding and regroups operation. The proposed scheme was tested against 9 images and proved to be effective in reducing the quantization errors and enhancing the compression performance. For instance, when the benchmark compression ratio (CR) is 0.5, the CR can be reduced by 5%(CR = 0.4453) ∼ 23%(CR = 0.2636), with the corresponding peak signal-to-noise ratio values consistently surpassing the benchmark. Furthermore, the execution of DNA compression and DNA dynamic encoding-decoding provided double guarantee for the algorithm's security. © 2024 IEEE.

关键词： Encoding (symbols)

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Web Inspection Algorithm of Low Contrast Paper Defects Using Gabor Filter 6th

Web Inspection Algorithm of Low Contrast Paper Defects Using...

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6th International Conference on Computing, Control, and Industrial Engineering, CCIE 2021

作者： Qu, Yunhui Tang, Wei Su, Yulei Cheng, Shuangshuang Computer Teaching and Research Section Xi’an Medical University Shaanxi Xi’an China College of Electric and Information Engineering Shaanxi University of Science and Technology Shaanxi Xi’an China

ISBN: (纸本)9789811939266

Aiming at low detection rate problem of existing paper defects detection algorithms for low contrast paper defects, a low contrast paper defect detection algorithm based on Gabor Filter and Laplasian is proposed. To solve the problem of low contrast, Gabor filter and Gaussian filter were used to filter out noise and enhance contrast. Then Laplasian operator and mathematical morphology operation were used to obtain the complete edge of paper defect. Finally, the experimental results show that the algorithm could effectively resist the disturbance of paper texture, had a high detection rate for low contrast paper defects and at the same time, for the high contrast paper defects, it still maintained high detection accuracy. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Gabor filters

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On Treatment Patterns for Modeling Medical Treatment Processes in Clinical Practice Guidelines

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China Communications 2021年第11期18卷 197-209页

作者： Liqin Yang Liang Zhang School of Computer Science Fudan UniversityShanghai 200438China Shanghai Key Laboratory of Data Science Shanghai 200438China Institute of Intelligent Electronics and Systems Shanghai 200438China Computer Teaching and Research Section Shanghai University of Traditional Chinese MedicineShanghai 201203China

Clinical practice guidelines(CPGs)contain evidence-based and economically reasonable medical treatment *** medical treatment processes in healthcare information systems can assist the treatment *** this end,business process modeling technologies have been exploited to model medical treatment ***,medical treatment processes are usually flexible and *** reduce the effort in modeling,we summarize several treatment patterns(i.e.,frequent behaviors in medical treatment processes in CPGs),and represent them by three process modeling languages(i.e.,BPMN,DMN,and CMMN).Based on the summarized treatment patterns,we propose a pattern-based integrated framework for modeling medical treatment processes.A modeling platform is implemented to support the use of treatment patterns,by which the feasibility of our approach is *** empirical analysis is discussed based on the coverage rates of treatment *** from interviewed physicians in a Chinese hospital shows that executable medical treatment processes of CPGs provide a convenient way to obtain guidance,thus assisting daily work for medical workers.

关键词： clinical practice guidelines treatment patterns process modeling BPMN DMN CMMN

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Medical Treatment Process Modeling Based on Process Mining and Treatment Patterns

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China Communications 2021年第12期18卷 332-349页

作者： Liqin Yang Guosheng Kang Liang Zhang School of Computer Science Fudan UniversityShanghai 200438China Shanghai Key Laboratory of Data Science Shanghai 200438China Institute of Intelligent Electronics and Systems Shanghai 200438China Computer Teaching and Research Section Shanghai University of Traditional Chinese MedicineShanghai 201203China School of Computer Science and Engineering Hunan University of Science and TechnologyXiangtan 411201China

***-periments on a synthetic log of the non-secondary hy-pertension MTP and empirical findings demonstrate the effectiveness of our *** results show that the process mining in our approach framework can automatically generate more accurate MTP mod-els,and the subprocess models based on treatment pat-terns make the models easy to understand.

关键词： business process modeling medical treat-ment processes treatment patterns clinical practice guidelines

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Adaptive Compression-Encryption Scheme for Medical Image Based on Improved Compressive Sensing and Deoxyribonucleic Acid Coding-Compression

Adaptive Compression-Encryption Scheme for Medical Image Bas...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Xianglian Xue Haiyan Jin Changjun Zhou School of Computer Science and Engineering Xi’an University of Technology Xi’an China Section of Computer Teaching and Research Shaanxi University of Chinese Medicine Xianyang China Shaanxi Key Laboratory for Network Computing and Security Technology Xi’an China School of Computer Science and Technology Zhejiang Normal University Jinhua China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

关键词： Image coding Heuristic algorithms DNA Transforms Benchmark testing Encoding Sensors Compressed sensing Secure storage Biomedical imaging

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Paper Defects Classification Based on VGG16 and Transfer Learning

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Palpu Chongi Gisul/Journal of Korea Technical Association of the Pulp and Paper Industry 2021年第2期53卷 5-14页

作者： Yun-Hui, Qu Tang, Wei Feng, Bo Computer Teaching and Research Section Xi’an Medical University Xi’an Shaanxi710021 China Department of Electric and Control Engineering Shaanxi University of Science & Technology Xi’an Shaanxi710021 China Department of Electric and Control Engineering Shaanxi University of Science & Technology Xi’an Shaanxi710021 China

There are some problems in traditional paper defects classification, such as the poor generalization performance, less types of recognition, and insufficient recognition accuracy. The deep learning method provides a new scheme for paper defects classification. However, due to the small sample size of paper defect images set, the over fitting phenomenon is easy to appear in the training process. Aiming this problem, a transfer learning method based on convolutional neural network model is ***, freezing the first seven construction layers of VGG16 network which has been trained by ImageNet, and fine tune the rest convolution layers with the paper defect images set to complete the feature extraction;Secondly, the full connection layers for classification are improved to meet the needs of paper defects classification;Finally, transfer learning strategy is adopted in the training process to improve the efficiency. The experimental results demonstrate that the paper defects classification proposed in our approach can improve the efficiency and accuracy of paper defects recognition. The approach will beneficial for the web inspection process. © 2021 Korean Technical Assoc. of the Pulp and Paper Industry. All rights reserved.

关键词： Efficiency

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6D Pose Estimation Based on Edge-Enhanced Point Pair Features for Surgical Navigation 8

6D Pose Estimation Based on Edge-Enhanced Point Pair Feature...

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8th International Conference on Virtual Reality, ICVR 2022

作者： Liu, Chenyi Chen, Fei Deng, Lu Yi, Renjiao Zheng, Lintao Zhu, Chenyang School of Computer Science National University of Defense Technology Changsha China Second XiangYa Hospital Central South University Department of Spine Surgery Changsha China Clinical Nursing Teaching and Research Section Second Xiang Ya Hospital Changsha China College of Meteorology and Oceanography National University of Defense Technology Changsha China

ISBN: (数字)9781665479110

ISBN: (纸本)9781665479110

This paper proposes an efficient 6D pose estimation method for the automatic spinal surgical navigation system. Visual-based pose estimation is challenging in realistic surgical scenes due to the human spine's geometric complexity and symmetric ambiguity. Instead of considering the whole scene for pose estimation, we introduce a targeted down-sampling strategy that focuses more on edge area for efficient feature extraction of complex geometry. A pose hypothesis validation approach is then presented to resolve the symmetric ambiguity. Note that our method can also work on incomplete scenes since our sampling and validation do not require a whole model. We perform evaluations on two challenging datasets, which demonstrate the superiority of our method on pose estimation of geometrically complex, occluded, symmetrical objects. We also implemented a prototype of a surgical navigation system based on the proposed method, which may provide a viable option for improving the spinal clinical surgery system. © 2022 IEEE.

关键词： Geometry

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Web inspection algorithm for low contrast paper defects based on artificial bee colony optimization

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Palpu Chongi Gisul/Journal of Korea Technical Association of the Pulp and Paper Industry 2020年第2期52卷 43-51页

作者： Qu, Yun-Hui Tang, Wei Feng, Bo Department of Electric and Control Engineering Shaanxi University of Science and Technology Xi'an Shaanxi710021 China Computer Teaching and Research Section Xi'An Medical University Xi'an Shaanxi710021 China

Traditional paper defect detection algorithms have the problems of low detection rate and poor anti-interference ability for low contrast paper defects such as cracks and folds. Considering these problems, an algorithm of low contrast paper defects based on artificial bee colony optimization was presented. Firstly, the Gabor filter was used to eliminate the texture elements and enhance the contrast. Then, the optimal segmentation threshold of 2-D OSTU was obtained by taking the trace of the dispersion matrix of the filtered paper disease image as the objective function of the artificial swarm optimization. Finally, according to the best segmentation threshold, the paper image was detected by 2-D OSTU method. The simulation results indicated that this algorithm has the advantages of high detection rate, accurate positioning and good anti-disturbance performance for low contrast paper defects. © 2020 Korean Technical Assoc. of the Pulp and Paper Industry. All rights reserved.

关键词： Image segmentation

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An Algorithm for On-Line Image Segmentation of Multiple Paper Defects Based on Fast Two-Dimensional Threshold Method

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Palpu Chongi Gisul/Journal of Korea Technical Association of the Pulp and Paper Industry 2020年第4期52卷 28-37页

作者： Qu, Yun-Hui Tang, Wei Feng, Bo Department of Electric and Control Engineering Shaanxi University of Science & Technology Shaanxi Xi’an710021 China Computer Teaching and Research Section Xi’an Medical University Shaanxi Xi’an710021 China

The two-dimensional threshold segmentation algorithm is time-consuming and cannot detect multiple paper defects. Considering these problems, a fast two-dimensional threshold method for on-line segmentation of multiple paper defects was proposed. The image subtraction operation was used first to segment the image with multiple paper defects. Then dividing two-dimensional threshold into two one-dimensional thresholds was used to accelerate the segmentation. At the same time, according to the gray distribution characteristics of the paper defect image after subtraction, the search range of the threshold was narrowed, and the selection of the optimal threshold was further accelerated. Experimental results showed that the algorithm proposed in this paper can accurately and quickly detect multiple paper defects, and could be effectively used for real-time detection of the paper production process. © 2020 Korean Technical Assoc. of the Pulp and Paper Industry. All rights reserved.

关键词： Defects

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