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GP-PSENet: a group-related dilated and a parallel extensional dilation-wise residual encoder for scene text detection

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Neural computing and applications 2025年第10期37卷 7159-7181页

作者： Huang, Liwen Yang, Wenyuan Fujian Key Laboratory of Granular Computing and Application Minnan Normal University Fujian Zhangzhou363000 China School of Mathematics and Statistics Minnan Normal University Fujian Zhangzhou363000 China

At present, scene text detection is grabbing more and more attention as an offshoot of machine vision. However, due to the existing long types of text instances and complex background context, less exact localization and higher missed detection cases still remain in text detection domain. Accordingly, with the aim of tackling these two issues, we propose a text detector named GP-PSENet that comprises a combination of a group-related dilated encoder, a parallel extensional dilation-wise residual encoder and a mixed upsample. Firstly, feature maps of the lowest level processed by the backbone network are sent to a dilated encoder with group linkage. And the group residual module provides stratification to join group coefficients and dilated factors. This module can enhance the correctness of predictions about longer boundary boxes. Secondly, semantic information from the highest level is fed into a parallel extensional dilation-wise residual encoder. The extensional dilation-wise module is capable of obtaining diverse receptive fields by more parallel branches. And it can alleviate error detection from interfering material in the background. Thirdly, the feature maps processed in the second step are given to the mixed upsample module for transforming so as to the next fuse. Finally, the processed two-level feature maps are fused and sent to the progressive scale expansion algorithm for the final post-processing to gain the predicted coordinate points. Ablation experiments are conducted on CTW1500, ICDAR15, MSRA-TD500 and Total-Text datasets to confirm the availability of the proposed method. The values of precision on these datasets reach 86.24%, 87.84%, 73.98% and 90.48%. The proposed method is also competitive with other scene detection methods. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Computer vision

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Secure Sharing Data Integrity Audit Scheme with Dynamic User Groups in Cloud Storage

Journal of Network Intelligence

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Journal of Network Intelligence 2024年第3期9卷 1673-1692页

作者： Liu, Jia-Xian Huang, Hui Chen, Qun-Shan Huang, Zhen-Jie School of Computer Science Minnan Normal University Zhangzhou363000 China Fujian Key Laboratory of Granular Computing and Application Minnan Normal University Zhangzhou363000 China

With the wide application of cloud storage, users with limited resources send outsourced data to the cloud service provider. Shared data storage has become a vital application form in some cloud storage scenarios. Many existing shared data integrity audit schemes don’t consider the user’s access rights. The revoked user can still access the data in the group. Moreover, they cannot support the dynamism of the data, nor can they support data privacy and user identity protection from infringement by the validator. We propose a safe and feasible shared data audit scheme to solve several of the problems above. In our scheme, once the group user is revoked, he has no permission to access and download data. We also design a dynamic multi-tree data storage structure to realize the increase, deletion, and search of dynamic user groups and data. Not only that, but our scheme also supports identity privacy protection for group users and data privacy protection. Experimental data show that our scheme is more efficient and safer than previous schemes. Especially in calculating tag generation, we reduces the computing overhead by 50 %. © 2024, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Data integrity

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Secure Location Data Sharing Scheme with KN-tree in Mobile Online Social Network(SMOSNs)

Journal of Network Intelligence

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Journal of Network Intelligence 2023年第2期8卷 609-626页

作者： Liu, Hong-Yang Huang, Hui Chen, Qun-Shan Huang, Zhen-Jie Wu, Chen-Huang School of Computer Science Minnan Normal University Zhangzhou363000 China School of Computer Science Fujian Key Laboratory of Granular Computing and Application Minnan Normal University Zhangzhou363000 China Fujian Key Laboratory of Granular Computing and Application Minnan Normal University Zhangzhou363000 China Key Laboratory of Applied Mathematics of Fujian Province University Putian University Putian351100 China

Location data is a critical foundation for online social networks, and sharing location data is essential to improve the efficiency of online social services. However, location data often contains users’ sensitive information. How to protect users’ privacy is a crucial problem in the process of location data sharing. Many solutions have been proposed to preserve user privacy, such as deploying trusted base stations or using en-cryption. But the problem of privacy disclosure still exists. In particular, the existing schemes do not consider that malicious third-party nodes can obtain the user’s location data through rainbow attacks. The location server can guess the social relationship of users through their frequent location requests. In this paper, we propose a brand-new scheme to ensure safety in the entire process. Salt encryption has been adopted to ensure data security in the location recording phase, and Bloom filter to ensure privacy security in the data sharing phase. Moreover, we proposed a KN-tree structure to simplify the computational process of location updates. Finally, the theoretical analysis shows that our scheme is superior to the existing methods in terms of security and practicality. We also realize and analyze the efficiency of our proposed scheme. And using the KN-tree structure to save users’ location data can reduce the computing cost of the location server by about 27%. © 2023, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Social networking (online)

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Transversality on locally pseudocompact groups

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Frontiers of Mathematics in China 2021年第3期16卷 771-782页

作者： Fucai LIN Zhongbao TANG School of Mathematics and Statistics Minnan Normal UniversityZhangzhou363000China Fujian Key Laboratory of Granular Computing and Applications Minnan Normal UniversityZhangzhou363000China

Two non-discrete Hausdorff group topologiesτandδon a group G are called transversal if the least upper boundτ⋁δofτandδis the discrete *** this paper,we discuss the existence of transversal group topologies on locally pseudocompact,locally precompact,or locally compact *** prove that each locally pseudocompact,connected topological group satisfies central subgroup paradigm,which gives an affirmative answer to a problem posed by Dikranjan,Tkachenko,and Yaschenko[Topology Appl.,2006,153:3338–3354].For a compact normal subgroup K of a locally compact totally disconnected group G,if G admits a transversal group topology,then G/K admits a transversal group topology,which gives a partial answer again to a problem posed by Dikranjan,Tkachenko,and Yaschenko in ***,we characterize some classes of locally compact groups that admit transversal group topologies.

关键词： Transversal group topology locally pseudocompact group locally compact group locally precompact connected space central topological group

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Correction: DC-PSENet: a novel scene text detection method integrating double ResNet-based and changed channels recursive feature pyramid

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The Visual Computer 2024年第2期41卷 1413-1414页

作者： Huang, Liwen Liao, Shujiao Yang, Wenyuan Fujian Key Laboratory of Granular Computing and Application Minnan Normal University Zhangzhou China School of Mathematics and Statistics Minnan Normal University Zhangzhou China

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Competence-Based Knowledge Space Theory from the Perspective of Formal Concept Analysis

SSRN

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SSRN 2023年

作者： Huang, Baokun Li, Jinjin Li, Qifang Zhou, Yinfeng Chen, Huiqin School of Mathematics and Statistics Minnan Normal University Fujian Zhangzhou China Fujian Key Laboratory of Granular Computing and Applications Fujian Zhangzhou China School of Mathematics and Statistics Shaanxi Normal University Shaanxi Xi’an China

In this paper, competence-based knowledge space theory (CbKST) is approached from the perspective of formal concept analysis (FCA). The aim is to visualize the relationship between knowledge structure and competence structure. The skill map is transformed into a formal context, and the methodology for constructing the concept lattice is provided. Within a concept lattice, each node, referred to as a concept, embodies a knowledge state and a competence state as its extension and intention, respectively. It is demonstrated that the family of sets formed by the extensions of all concepts is exactly the knowledge structure delineated by the skill map via the corresponding model. Additionally, the difference set of the extensions of the proper sbuconcept-superconcept in a concept lattice reflects the master fringe of the individual knowledge state. A concept lattice is considered favorable if an individual can solve the items of the master fringe only by mastering one skill, and the sufficient and necessary conditions for favorable concept lattices are given. When skills have no inherent surmise relationship, the order in which they are learned can be arbitrary. From the perspective of effective learning, we propose a precedence relation between skills to guide the recommendation of personalized learning schemes. Moreover, it is proved that on a favorable concept lattice, there is a learning path that adheres to the principle of step-by-step and easy-to-difficult. © 2023, The Authors. All rights reserved.

关键词： Formal concept analysis

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On sobriety of Scott topology on dcpos

arXiv

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arXiv 2022年

作者： Xu, Xiaoquan Fujian Key Laboratory of Granular Computing and Applications School of Mathematics and Statistics Minnan Normal University Zhangzhou363000 China

In this paper, we mainly investigate the conditions under which the Scott topology on the product of two posets is equal to the product of the individual Scott topologies and under which the Scott topology on a dcpo is sober. Some such conditions are *** Codes 54D99, 54B20, 06B30, 06B35 Copyright © 2022, The Authors. All rights reserved.

关键词： Topology

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A decentralized data integrity auditing scheme for cloud storage

A decentralized data integrity auditing scheme for cloud sto...

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Data Security and Privacy Protection (DSPP), International Conference on

作者： Jiaxian Liu Hui Huang Qunshan Chen Zhenjie Huang School of Computer Science Minnan Normal University Zhangzhou Fujian China Fujian Key Laboratory of Granular Computing and Application Minnan Normal University Zhangzhou Fujian China

Cloud storage service providers offer remote data storage services, and users verify the integrity of the outsourced data through a fixed third-party auditor. However, a single third-party auditor may collaborate with other entities, which raises security problems. In this paper, we propose a decentralized integrity auditing scheme with multiple auditors participating, which solves the single point of failure problem caused by a single third-party auditor. However, using multiple auditors for auditing increases the communication overhead between cloud service providers and verifiers. To solve this problem, we introduce the concept of non-interactive public provable data ownership to reduce the interaction between them. We also design a new reward and punishment mechanism to motivate entities to participate honestly in auditing. The theoretical analysis and experimental evaluation show that our scheme is feasible and effective.

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Consistency correction of echo intensity data for multiple radar systems and its application in quantitative estimation of typhoon precipitation

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Frontiers of Earth Science 2022年第1期16卷 99-108页

作者： Shuai ZHANG Jing HAN Bingke ZHAO Zhigang CHU Jie TANG Limin LIN Xiaoqin LU Jiaming YAN Shanghai Typhoon Institute China Meteorological AdministrationShanghai 200030Chin Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Key Laboratory for Aerosol-Cloud-Precipitation(China Meteorological Administration)Nanjing University of Information Science&TechnologyNanjing 210044China Hainan Institute of Meteorological Sciences Haikou 570203China Key Laboratory of South China Sea Meteorological Disaster Prevention and Mitigation of Hainan Province Haikou 570203China Fujian Key Laboratory of Severe Weather Fuzhou 350001China Fujian Key Laboratory of Granular Computing and Application Minnan Normal UniversityZhangzhou 363000China

Calibration error is one of the primary sources of bias in echo intensity measurements by ground-based radar *** errors cause data discontinuity between adjacent radars and reduce the effectiveness of the radar *** Global Precipitation Measurement Kuband Precipitation Radar(GPM KuPR)has been shown to provide stable long-term *** this study,GPM KuPR observations were converted to S-band approximations,which were then matched spatially and temporally with ground-based radar *** measurements of stratiform precipitation below the melting layer collected by the KuPR during Typhoon Ampil were compared with those of multiple radar systems in the Yangtze River Delta to determine the deviations in the echo intensity between the KuPR and the ground-based radar *** echo intensity data collected by the ground-based radar systems was corrected using the KuPR observations as reference,and the correction results were verified by comparing them with rain gauge *** was found that after the correction,the consistency of the echo intensity measurements of the multiple radar systems improved significantly,and the precipitation estimates based on the revised ground-based radar observations were closer to the rain gauge measurements.

关键词： calibration error ground-based radar reflectivity correction precipitation estimates

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Incremental Cognitive Learning Approach Based on Concept Reduction

SSRN

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SSRN 2024年

作者： Liang, Taoju Lin, Yidong Li, Jinjin Wang, Qijun School of Mathematics and Statistics Minnan Normal University Zhangzhou363000 China Institute of Meteorological Big Data-Digital Fujian Minnan Normal University Zhangzhou363000 China Fujian Key Laboratory of Granular Computing and Applications Minnan Normal University Zhangzhou363000 China

Concept-cognitive learning (CCL) offers an innovative approach to classification, and concept reduction serves as a powerful method for compressing data. Nonetheless, most existing CCLs tend to incur information loss during the compression of concept space. On the other hand, current incremental CCLs have limited capacity to effectively utilize newly acquired knowledge. In view of these observations, in this article, we propose a novel incremental CCL method based on concept reduction for dynamic classification. To enhance the efficiency of knowledge acquisition, recover degree is developed to obtain concept reduction from granular concept space. Subsequently, the updating mechanism for concept reduction is explored in dynamic environments. For label recognition, a learning method based on concept reduction is discussed and an incremental learning mechanism for dynamic increased data is further constructed. Empirical studies on twelve datasets from UCI reveal the effectiveness and efficiency of proposed model. © 2024, The Authors. All rights reserved.

关键词： Efficiency

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