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Topic Controlled Steganography via Graph-to-Text Generation

Computer Modeling in engineering & Sciences 2023年第7期136卷 157-176页

作者： Bowen Sun Yamin Li Jun Zhang Honghong Xu Xiaoqiang Ma Ping Xia School of Computer Science and Information Engineering Hubei UniversityWuhan430062China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges UniversityYichang443002China Yichang Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges UniversityYichang443002China Department of CSIS Douglas CollegeNewWestminsterBCV3L 5B2Canada College of Computer and Information Technology China Three Gorges UniversityYichang443002China

Generation-based linguistic steganography is a popular research area of information *** text generative steganographic method based on conditional probability coding is the direction that researchers have recently paid attention ***,in the course of our experiment,we found that the secret information hiding in the text tends to destroy the statistical distribution characteristics of the original text,which indicates that this method has the problem of the obvious reduction of text quality when the embedding rate increases,and that the topic of generated texts is uncontrollable,so there is still room for improvement in *** this paper,we propose a topic-controlled steganography method which is guided by graph-to-text *** proposed model can automatically generate steganographic texts carrying secret messages from knowledge graphs,and the topic of the generated texts is *** also provide a graph path coding method with corresponding detailed algorithms for graph-to-text *** from traditional linguistic steganography methods,we encode the secret information during graph path coding rather than using conditional *** test our method in different aspects and compare it with other text generative steganographic *** experimental results show that the model proposed in this paper can effectively improve the quality of the generated text and significantly improve the concealment of steganographic text.

关键词： Information hiding linguistic steganography knowledge graph topic controlled text generation

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An Attention Mechanism-based Relation Network for Few-Shot Image Classification 25

An Attention Mechanism-based Relation Network for Few-Shot I...

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25th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2022

作者： Tang, Tinglong Zhao, Chenxi Wu, Yirong China Three Gorges University Hubei Key Laboratory Intelligent Vision Based Monitoring for Hydroelectric Engineering Yichang Key Laboratory of Intelligent Medicine College of Computer and Information Technology Yichang Hubei China

ISBN: (纸本)9781665405270

The key to solving the few-shot image classification problem is learning image category information from a handful of image samples. Few-shot image classification can easily cause overfitting problems that impact classification performance due to insufficient labeled data. In this paper, an attention mechanism-based relation network model for few-shot image classification is proposed. Inspired by classic methods of relation networks for few-shot learning, the attention mechanism in a convolutional block attention mechanism (CBAM) for metric learning is utilized in the feature extraction network. Then, an update strategy selecting a validation set during the training is adopted to reduce the possibility of overfitting. Through comparison experiments on different datasets, the results demonstrate that our model has better accuracy than traditional methods. © 2022 IEEE.

关键词： Image classification

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High Security Frequency Hopping Communication for the Power Internet of Things

High Security Frequency Hopping Communication for the Power ...

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2023 International Conference on intelligent Communication and Computer engineering, ICICCE 2023

作者： Liu, X. Zeng, M. Deng, H. Peng, S. Liu, C. China Three Gorges University State Grid Yichang Electric Power Supply Company Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China China Three Gorges University Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China State Grid Yichang Electric Power Supply Company China

ISBN: (纸本)9798350395617

With the deepening of digital transformation of power industry, more and more power devices are being connected to wireless communication networks. Due to the broadcasting characteristics and openness of wireless channels, the security of power data transmission is facing serious challenges, especially for devices with limited resources. Frequency hopping (FH) technique is extensively utilized in high secure communications due to its effectiveness in mitigating interference and ensuring confidentiality. However, the increasing sophistication of electronic attacks pose a great challenge to the use of sequences aided by number theory and chaos theory. Considering the power devices with limited resources, a FH sequence generation scheme for power Internet of Things (IoT) with the aid of Eslice lightweight encryption algorithm is proposed, which achieves a balance between efficiency and security, and resist differential cryptanalysis with limited resources. Meanwhile, the proposed scheme outperforms better than the available algorithms in terms of most test metrics. Therefore, it can be seen that the proposed scheme is able to obtain secure information transmission with low resource consumption, and provide an efficient solution for wireless transmission of resource limited devices in the power IoT. © 2023 IEEE.

关键词： Internet of things

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A Defect Detection Method based on Parallel Multiple AutoEncoders 26

A Defect Detection Method Based on Parallel Multiple AutoEnc...

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26th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2023

作者： Wu, Yirong He, Wenjing Sun, Shuifa Tang, Tinglong China Three Gorges University Yichang Key Laboratory of Intelligent Medicine College of Computer and Information Technology Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering Yichang443002 China

ISBN: (纸本)9798350331684

There is an urgent need for industrial manufacturing to fully integrate with emerging technologies to build enterprise core competitiveness. Currently, existing methods have difficulty meeting the high-precision and stability practical requirements with diversified industrial products. In this study, a PMAE (Parallel Multiple AutoEncoders, PMAE) model is proposed, which is designed with parallel multiple encoders based on the AutoEncoder framework. It uses the network of parallel multiple encoders with different encoder structures to obtain latent features that have rich and precise semantic information. A consistency objective function is proposed to make the PMAE network converge stably and rapidly, which allows the aggregated latent features to be simultaneously reconstructed and adaptively classified. Compared with the state-of-the-art methods on the NEU-CLS, Data-Crack, and DAGM2007 datasets, our method achieves the most stable performance and the highest accuracy in different defect detection tasks. © 2023 IEEE.

关键词： Learning systems

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Pure Detail Feature Extraction Network for Visible-Infrared Re-Identification

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intelligent Automation & Soft Computing 2023年第8期37卷 2263-2277页

作者： Jiaao Cui Sixian Chan Pan Mu Tinglong Tang Xiaolong Zhou Zhejiang University of Technology Hangzhou310023China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering The College of Computer and InformationChina Three Gorges UniversityYichang443002China The College of Electrical and Information Engineering Quzhou UniversityQuzhou324000China

Cross-modality pedestrian re-identification has important appli-cations in the field of *** to variations in posture,camera per-spective,and camera modality,some salient pedestrian features are difficult to provide effective retrieval ***,it becomes a challenge to design an effective strategy to extract more discriminative pedestrian *** many effective methods for detailed feature extraction are proposed,there are still some shortcomings in filtering background and modality *** further purify the features,a pure detail feature extraction network(PDFENet)is proposed for *** includes three modules,adaptive detail mask generation module(ADMG),inter-detail interaction module(IDI)and cross-modality cross-entropy(CMCE).ADMG and IDI use human joints and their semantic associations to suppress background noise in *** guides the model to ignore modality noise by generating modality-shared feature ***,ADMG generates masks for pedestrian details based on pose *** are used to suppress background information and enhance pedestrian detail ***,IDI mines the semantic relations among details to further refine the ***,CMCE cross-combines classifiers and features to generate modality-shared feature labels to guide model *** ablation experiments as well as visualization results have demonstrated the effectiveness of PDFENet in eliminating background and modality *** addition,comparison experi-ments in two publicly available datasets also show the competitiveness of our approach.

关键词： Person re-identification multimedia image retrieval

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Haar-like and HOG fusion based object tracking 15

Haar-like and HOG fusion based object tracking

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15th Pacific-Rim Conference on Multimedia, PCM 2014

作者： Xia, Chong Sun, Shui-Fa Chen, Peng Luo, Heng Dong, Fang-Min Institute of Intelligent Vision and Image Information China Three Gorges University YiChangHuBei443002 China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges University Yichang443002 China

ISBN: (纸本)9783319131672

Only unitary feature for object is adopted in the conventional tracking system, making it difficult for robust tracking. Regarding the characteristic of both Haar-like and HOG features, a tracking algorithm fusing these two features is proposed: using the Haar-like features for the structure of the object and HOG features for the edge. A mixed feature pool is constructed with these two features. The On-line Boosting feature selection framework is adopted to select out the notable features, and update these features on line to realize the optimal selection. Four representative videos are used to test the performance of the proposed algorithm in the aspect of illumination change, tacking small targets, complex motion of the object, similar object interference during tracking and so on. Statistical analysis Results of the error show that the tracking system using the fused features outperforms the system using either of the two features. © Springer International Publishing Switzerland 2014.

关键词： Tracking (position)

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Construction Site Fence Recognition Method based on Multi-Scale Attention Fusion ENet Segmentation Network 35

Construction Site Fence Recognition Method Based on Multi-Sc...

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35th International Conference on Software engineering and Knowledge engineering, SEKE 2023

作者： Zhang, Xing Tang, Tinglong Wu, Yirong Quan, Tingwei Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges University Yichang China Wuhan National Laboratory for Optelectronics Huazhong University of Science and Technology Wuhan China

In this paper, we propose a fence recognition method based on the ENet (Efficient neural Network) segmentation network to address the problems of traditional segmentation networks, which have poor performance in recognizing fences with a large range of scale variations and hollow structures. Firstly, a multi-scale attention fusion ENet segmentation network is designed, which is trained using the fence with obvious color features. Then, a morphological algorithm is used to process the predicted image to restore the fence segmentation results. The designed multi-scale attention fusion segmentation network performs better on fence datasets than traditional methods. In addition, the activation function Leaky_Relu6 further enhances the stability and generalization ability of the network. The experiments are conducted on 540 fence images from different construction sites, and the computed IoU is 90%. The processing speed is about 28 frames per second. The experimental results show that our proposed network outperforms traditional segmentation algorithms in fence recognition performance, and achieves robustness in different construction scenarios while meeting the requirements of both accuracy and speed. © 2023 Knowledge Systems Institute Graduate School. All rights reserved.

关键词： Image segmentation

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Compressive tracking with locality sensitive histograms features

Compressive tracking with locality sensitive histograms feat...

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2017 IEEE International Conference on Robotics and Automation, ICRA 2017

作者： Chan, Sixian Zhou, Xiaolong Zhang, Zhuo Chen, Shengyong College of Computer Science and Technology Zhejiang University of Technology Hangzhou China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges University Yichang China

ISBN: (纸本)9781509046331

Currently, Compressive Tracking (CT) method has drawn great attention because of its high efficiency. However, it cannot well deal with some appearance variations due to its limitations of feature expression and it only uses a fixed parameter to update the appearance model. In order to handle such matters, we propose an adaptive CT method that combines the predicted target position with CT based on Locality Sensitive Histograms (LSH) features. Our method significantly improves CT in four aspects. First, the efficient illumination invariant features extracted based on LSH are used to represent an effective appearance model that is robust to illumination changes. Second, the color attributes tracker is adopted to predict the target position for re-building the new weighted discriminant function which brings in the color information to make up for the inadequacy of Haar-like characteristics. Third, a new model update mechanism is proposed to preserve the stable features while avoid the noisy appearance variations during tracking. Fourth, a trajectory rectification method is employed to refine the tracking location when possible inaccurate tracking occurs. Finally, we show that our tracker achieves state-of-the-art performance in a comprehensive evaluation over 47 challenging color sequences. © 2017 IEEE.

关键词： Graphic methods

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Photo linker: A system for finding your old photos based on fragmentary memories 7

Photo linker: A system for finding your old photos based on ...

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7th International Conference on Internet Multimedia Computing and Service, ICIMCS 2015

作者： Wei, Shikui Yang, Fan Ruan, Tao Liu, Ruoyu Zhu, Zhenfeng Zhao, Yao Institute of Information Science Beijing Jiaotong University Beijing100044 China Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges University Yichang Hubei443002 China

ISBN: (纸本)9781450335287

With the rapid spread of image capture devices, the size of family album grows quickly up. It is difficult for family members to find out an expected photo just based on their fragmentary memory. In this paper, we attempt to develop a system named Photo Linker, to help people quickly get their expected photos by fully exploring the clues remembered by themselves. The key idea is to build the relationship among all photos by shared faces and scenes. The system includes three key components: (1) face detection and recognition;(2) scene classification;(3) association searching. In particular, an algorithm called "Association Correction" based on FP-Growth is discovered to improve the face recognition rate of family members. Moreover, a friendly interface is designed and implemented to facilitate the photo searching process. The experimental results show that the system can effectively and efficiently build the relationship among photos and make the photo finding process more convenient. © 2015 ACM.

关键词： Data mining

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Covert Communication in Power Internet of Things 3

Covert Communication in Power Internet of Things

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3rd International Conference on High Performance Computing and Communication engineering, HPCCE 2023

作者： Li, Yang Zhao, Lingchu Zhu, Jia Liu, Yonglin Ding, Jian Yang, Jia Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges University Hubei Yichang443002 China State Grid Yichang Electric Power Supply Company Hubei Yichang443002 China

ISBN: (数字)9781510674653

ISBN: (纸本)9781510674646

Covert communication refers to achieving high-level secure transmission by protecting communication behaviour. This paper primarily centres on the examination of covert communication in the scene of the power Internet of Things (PIoT). Specifically, we explore the scenario where power users (PU) transmit information to the master station (MS) while being exposed to potential eavesdropping. In addition, we assume that Willie has noise uncertainty when detecting communication behaviour, which makes it difficult for Willie to accurately detect communication behaviour, and significantly affects the detection error probability (DEP) of Willie and the overall covert performance of the proposed model. It is worth noting that the simulation results indicate that the presence of noise uncertainty can enable MS and PU to successfully achieve covert transmission. By leveraging this uncertainty, MS and PU can effectively protect their communication behaviour and minimize the risk detected by potential Willie, which provides a solution for high-level secure communication in the field of PIoT and effectively protects the privacy of PU. © 2024 SPIE.

关键词： Internet of things

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