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152 results on '"Qi, Yongjun"'

1. Application of Artificial Intelligence Technology in Text Recognition and Detection Algorithms

Author

Liang, Junxia, Qi, Yongjun, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Hung, Jason C., editor, Yen, Neil, editor, and Chang, Jia-Wei, editor

Published
2024
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2. Exploration on Text Detection Optimization Algorithm Based on Neural Network Technology

Author

Liang, Junxia, Qi, Yongjun, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Hung, Jason C., editor, Yen, Neil, editor, and Chang, Jia-Wei, editor

Published
2024
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6. Application of Artificial Intelligence Technology in Big Data Nining

Author

Zhou, Xueyun, Qi, Yongjun, Tang, Hailin, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Hung, Jason C., editor, Chang, Jia-Wei, editor, and Pei, Yan, editor

Published
2023
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7. A Text Detection and Recognition System Based on Dual-Attention Mechanism with Artificial Intelligence Technology

Author

Qi, Yongjun, Li, Chenggao, Huang, Li, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Hung, Jason C., editor, Chang, Jia-Wei, editor, and Pei, Yan, editor

Published
2023
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8. Double Attention Mechanism Text Detection and Recognition Based on Neural Network Algorithm

Author

Qi, Yongjun, Tang, Hailin, Huang, Li, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Hung, Jason C., editor, Chang, Jia-Wei, editor, and Pei, Yan, editor

Published
2023
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19. Machine learning-based processing of unbalanced data sets for computer algorithms

Author

Zhou Qingwei, Qi Yongjun, Tang Hailin, and Wu Peng

Subjects
machine learning, unbalanced data sets, classification algorithm, data processing, computer algorithm, decision tree classification, Electronic computers. Computer science, QA75.5-76.95
Abstract

The rapid development of technology allows people to obtain a large amount of data, which contains important information and various noises. How to obtain useful knowledge from data is the most important thing at this stage of machine learning (ML). The problem of unbalanced classification is currently an important topic in the field of data mining and ML. At present, this problem has attracted more and more attention and is a relatively new challenge for academia and industry. The problem of unbalanced classification involves classifying data when there is insufficient data or severe category distribution deviations. Due to the inherent complexity of unbalanced data sets, more new algorithms and tools are needed to effectively convert a large amount of raw data into useful information and knowledge. Unbalanced data set is a special case of classification problem, in which the distribution between classes is uneven, and it is difficult to classify data accurately. This article mainly introduces the research on the processing method of computer algorithms based on the processing method of unbalanced data sets based on ML, aiming to provide some ideas and directions for the processing of computer algorithms based on unbalanced data sets based on ML. This article proposes a research strategy for processing unbalanced data sets based on ML, including data preprocessing, decision tree data classification algorithm, and C4.5 algorithm, which are used to conduct research experiments on processing methods for unbalanced data sets based on ML. The experimental results in this article show that the accuracy rate of the decision tree C4.5 algorithm based on ML is 94.80%, which can be better used for processing unbalanced data sets based on ML.

Published
2023
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35. Fuzzy system for image defect detection based on machine vision

Author

Lai, Yiqiang, Qi, Yongjun, and Zeng, Xianfeng

Abstract

With the continuous upgrading of the industrial field, the market's requirements for product quality are also increasing, which requires more accurate product monitoring equipment. This paper analyses the composition of the vision system, and compares the collected images with the defects under manual detection based on the non-local mean denoising algorithm, and the results meet the system requirements. The experimental results show that the image size is 140*141, the distortion rate is 0.992, the image size is 120*81, and the distortion rate is 0.703. This means that the larger the image size, the higher the distortion. Before the improved algorithm, a total of 47 defects were detected, while after the improved algorithm, a total of 83 defects were detected. It can be seen that when the algorithm is improved, the number of defect detections increases significantly.

Published
2024
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44. Application of Virtual Network Mapping Algorithm Based on Optimal Subnet in Enterprise Cost Accounting Platform.

Author

Wu, Haiyan, Li, Xiao, Qi, Yongjun, Tang, HaiLin, and Zhang, Shukun

Subjects
COST accounting, PRODUCT costing, PATTERN matching, ALGORITHMS, ACCOUNTING methods, BUSINESS enterprises, VIRTUAL networks
Abstract

The price of the product has a great impact on the market competitiveness of the product. The manager can adjust the operation strategy according to the cost information of the product, cut costs, adjust the market decision and make the product more competitive in the market. Therefore, the research of product costing method has a very important significance. Considering that the physical resources in the processing of the virtual network mapping (VNM) fragment embedded in the request are rejected, and the problem of physical resource usage is weakened, a VNM algorithm based on the optimal subnet edge matching algorithm is proposed. After the VNM request is coarsened to the subnet, the breadth-first search algorithm is used to create the physical subnet candidate set, and the constraints of the virtual node and the coarsening network topology are complied with. The simulation results show that the proposed algorithm reduces the number of link mapping hops and can improve the acceptance rate and cost-benefit ratio of virtual networks. First of all, this paper analyzes the research background of manufacturing cost calculation and the research situation at home and abroad, discusses the advantages and disadvantages of standard cost calculation and studies and analyzes the principles, advantages and disadvantages of standard cost calculation in daily business activities. Second, design a new mathematical accounting model based on the mathematical model of standard cost calculation in daily business activities. This combines the advantages of standard costing and time-based activity costing, and provides theoretical support for manufacturing companies to use this accounting method. Finally, the research results of this paper are summarized, and the shortcomings of this paper are analyzed. Cost accounting method needs to be further studied. [ABSTRACT FROM AUTHOR]

Published
2023
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47. Antitumor effects of conditioned media of human fetal dermal mesenchymal stem cells on melanoma cells

Author

Sun,Bencheng, Wang,Xiao, Pan,Yi, Jiao,Ya, Qi,Yongjun, Gong,Hongmin, and Jiang,Duyin

Subjects
PI3K/AKT signaling pathway, human fetal dermal mesenchymal stem cells, conditioned media, melanoma, apoptosis, MAPK signaling pathway, OncoTargets and Therapy, Original Research
Abstract

Bencheng Sun,1–3,* Xiao Wang,1–2,4,* Yi Pan,1–2,4 Ya Jiao,1,2 Yongjun Qi,1–2,4 Hongmin Gong,1–2,4 Duyin Jiang1–2,41Department of Emergency, The Second Hospital of Shandong University, Jinan, Shandong Province, People’s Republic of China; 2Department of Emergency and Department of Burns and Plastic Surgery, The Second Hospital of Shandong University, Jinan, Shandong Province, People’s Republic of China; 3Department of Burn and Plastic Surgery, Linyi People’s Hospital, Linyi, Shandong Province, People’s Republic of China; 4School of Medicine, Shandong University, Jinan, Shandong Province, People’s Republic of China*These authors contributed equally to this workBackground: Malignant melanoma is the most lethal form of cutaneous tumor and has a high metastatic rate and motility capacity. Owing to the poor prognosis, it is urgent to seek an effective therapeutic regimen. Human mesenchymal stem cells (MSCs) can home to tumor cells and have been shown to play important roles in both promoting and inhibiting tumor development. Fetal dermal MSCs (FDMSCs), derived from fetal skin are a novel source of MSCs. Nevertheless, the antitumor capacity of FDMSCs on malignant melanoma is not clearly understood.Materials and methods: FDMSCs were extracted from the dorsal skin of fetal tissues. A375 melanoma cells lines were obtained from American Type Culture Collection. The effects of conditioned media from FDMSCs (CM-FDMSC) on A375 melanoma cells were tested in vivo using tumor formation assay and in vitro using cell viability, 5-ethynyl-2ʹ-deoxyuridine incorporation, flow cytometry, TdT-mediated dUTP Nick-End Labeling (TUNEL), wound healing, transwell invasion, and Western blotting.Results: CM-FDMSC inhibited A375 tumor formation in vivo. In vitro, CM-FDMSC inhibited the tumor-related activities of A375 melanoma cells, as evidenced reductions in viability, migration, and invasion. CM-FDMSC-treated A375 cells showed decreased phosphatidylinositol 3-kinase (PI3K), protein kinase B (AKT), and extracellular signal-regulated kinase (ERK) phosphorylation, and up-regulation of Bcl-2-Associated X (BAX) and down-regulation of B-cell lymphoma-2 (BCL-2) expression.Conclusion: CM-FDMSC can inhibit the tumor-forming behaviors of A375 melanoma cells and inhibit PI3K/AKT and mitogen-activated protein kinase signaling to shift their BCL-2/BAX ratio toward a proapoptotic state. Identification of the bioactive components in CM-FDMSC will be important for translating these findings into novel therapies for malignant melanoma.Keywords: human fetal dermal mesenchymal stem cells, melanoma, conditioned media, apoptosis, PI3K/AKT signaling pathway, MAPK signaling pathway

Published
2019

48. Implementation of filtering method of active optical displacement sensor based on ZYNQ

Author

Wusen Li, Weiqi Li, Wenjian Chen, and Qi Yongjun

Subjects
Signal processing, business.industry, Computer science, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Wavelet transform, Active optics, Signal, Displacement (vector), LAMOST, Adaptive filter, Wavelet, Computer vision, Artificial intelligence, business
Abstract

China’s LAMOST telescope is the most powerful spectroscopic measurement telescope for studying large field of view and large sample astronomy. It combines the world’s leading splicing mirror technology with thin mirror technology for the first time, breaking through the inability of previous astronomical instruments to combine large clear apertures and wide The bottleneck of the field of view. In order to more accurately detect the movement between the sub-mirrors of large-aperture telescopes, it is necessary to install a precise sensor at the edge of the sub-mirror to detect the movement between the sub-mirrors, and then adjust the mirror displacement in time through the force actuator under the mirror to obtain more Good image quality. Due to the particularity of the mirror surface, there are strict requirements on the displacement measurement accuracy of the sensor. Its research focuses on the acquisition and filtering of sensor displacement signals. In order to extract useful digital signals from strong noises and improve the signal-to-noise ratio (SNR) of the digital signals output by the detection system, this paper proposes a dual-channel digital filtering algorithm combining improved four-entry wavelet and adaptive filtering. By improving the four-entry wavelet algorithm, the algorithm improves the reconstruction capability and linearity while taking into account the multi-resolution characteristics of the traditional wavelet transform algorithm, and ensures the continuity of the wavelet coefficients at the threshold; and the second channel collects the high The frequency characteristic noise signal is processed again through adaptive filtering, and finally a sensor displacement signal with a higher signal-to-noise ratio (SNR) is obtained. After the front-end algorithm development is completed, the displacement signal acquisition and processing system is realized through the ZYNQ-7000 development platform, including AD conversion, digital filtering, signal transmission and LCD screen display, etc., and the Gui interface program is written using Matlab to convert the displacement signal Real-time display and save records on the PC side. The entire experiment of the displacement sensor was carried out at the Nanjing Institute of Astronomical Optics Technology, Chinese Academy of Sciences. The results show that the digital signal-to-noise ratio (SNR) processed by the algorithm is 20.7% higher than that of the traditional wavelet algorithm. The root mean square error (RMSE) of the fitted displacement curve is reduced by 19.8% on average, and the running time was reduced by 50%. It shows that the algorithm is accurate and fast, and its entire signal processing system has important application significance for the research of displacement sensors between splicing mirrors of large astronomical telescopes.

Published
2021

49. Aidi Injection as Adjuvant Drug Combined with Chemotherapy in Treatment of Breast Cancer: A Systematic Meta-Analysis

Author

Wu, Chenhao, Qi, Yongjun, Zhou, Juan, Yao, Chen, Miao, Min, and Cheng, Chen

Subjects
Article Subject
Abstract

Objective. To compare the efficacy and safety of combination of Aidi injection and chemotherapy and chemotherapy alone in treatment of breast cancer. Methods. The related control and randomized studies till August 1st, 2020, were retrieved in the database including PubMed, Embase, Cochrane Library, CNKI, CBM, Wang-Fang, and VIP. Primary outcomes were response rate (RR) and performance status (KPS) improvement rate; secondary outcomes were rate of adverse drug reactions (ADR) including myelosuppression, digestive tract reaction, liver dysfunction, and cardiac toxicity. Review Manager 5.3 was used in the present analysis. Results. In total, 20 studies (18 articles) were included in the present analysis. RR (OR 1.76 (1.32, 2.35); p=0.0001) and KPS improvement rate (OR: 2.68 (1.34, 6.46); p=0.007) in Aidi injection plus chemotherapy group were significantly higher than those of chemotherapy alone group. Addition of Aidi injection significantly reduced the rate of myelosuppression, digestive tract reaction, leukocyte decrease, II-IV cardiac function abnormality, atrial dysrhythmia, ventricular arrhythmia, ST segment T wave inversion, and abnormal ECG (all p

Published
2021
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