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Optical encryption of gray image based on CS and CGH with double chaotic system 5

Optical encryption of gray image based on CS and CGH with do...

引用

5th World Conference on Mechanical engineering and Intelligent Manufacturing, WCMEIM 2022

作者： Zhao, Xueyan Zhang, Zhao Niu, Shuqi Tian, Xintong School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan China

ISBN: (纸本)9781665473699

In this paper, a novel image encryption algorithm is proposed by combining Logistic chaotic map, 4D NHS hyperchaotic system, compressed sensing (CS), computer generated hologram (CGH) and two-dimensional discrete cosine transform (DCT). Firstly, the gray image is sparse represented by two-dimensional discrete cosine transform (DCT). The sparse matrix obtained by index sort scrambling is scrambled. For further encryption, the pixel scrambling uses the Logistic chaotic system to generate the scrambling vector. Subsequently, CGH encryption was performed and the Logistic chaotic map and 4D NHS hyperchaotic system were used as double keys to obtain the final encrypted picture. © 2022 IEEE.

关键词： Compressed sensing

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Research on ship detection of optical remote sensing image based on Yolo V5

Research on ship detection of optical remote sensing image b...

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2021 International Conference on Intelligent Power and Systems, ICIPS 2021

作者： Sun, X.M. Zhang, Y.J. Wang, H. Du, Y.X. School of Computer Science and Software Engineering University of Science and Technology Liao Ning China

In order to achieve ship target detection based on remote sensing images in complex backgrounds, this paper proposes a ship target detection algorithm based on YOLO V5. First, the improved Kmeans is used to cluster the data set, DIOU_loss is used for the candidate frame selection strategy, and finally the channel attention mechanism is introduced. The experimental results show that under the same conditions, the improved network has a slight decrease in detection speed compared with the original YOLOv5 network, and the effect of images with densely distributed small targets is significantly improved. On the same test set, the accuracy rate is reduced by 3.84%, the recall rate is increased by 32.73%, and mAP is increased by 22.48%. © Published under licence by IOP Publishing Ltd.

关键词： Image enhancement

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Critical Infrastructure Security Goes to Space: Leveraging Lessons Learned on the Ground

Critical Infrastructure Security Goes to Space: Leveraging L...

引用

Accelerating Space Commerce, Exploration, and New Discovery Conference, ASCEND 2023

作者： Ellis, Tim Hitaj, Briland Lindqvist, Ulf Shands, Deborah Tinnel, Laura DeBruhl, Bruce Computer Science Laboratory SRI International California Polytechnic State University United States Computer Science and Software Engineering Department California Polytechnic State University United States

ISBN: (数字)9781624107054

ISBN: (纸本)9781624107054

Space systems enable essential communications, navigation, imaging and sensing for a variety of domains, including agriculture, commerce, transportation, and emergency operations by first responders. Protecting the cybersecurity of these critical infrastructure systems is essential. While the space environment brings unique constraints to managing cybersecurity risks, lessons learned about risks and effective defenses in other critical infrastructure domains can help us to design effective defenses for space systems. In particular, discoveries regarding cybersecurity for industrial control systems (ICS) for energy, manufacturing, transportation, and the consumer and industrial Internet of Things (IoT) offer insights into cybersecurity for the space domain. This paper provides an overview of ICS and space system commonalities, lessons learned about cybersecurity for ICS that can be applied to space systems, and recommendations for future research and development to secure increasingly critical space systems. © 2023, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Cybersecurity

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Intelligent Vocal Training Assistant System 2nd

Intelligent Vocal Training Assistant System

引用

2nd EAI International Conference on Edge Computing and IoT: Systems, Management and Security, ICECI 2021

作者： Li, Yihong Luo, Chengzhe College of Computer Science and Software Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9783031042300

In professional vocal training, a way to evaluate the quality of vocalization is often needed. In order to solve various problems caused by the lack of professional instructors, a vocal training system for detecting the closed state of the vocal cords is proposed. We have proposed a robust vocal training system for the detection of the closed state of the vocal cords on the mobile terminal, which can analyze the closure of the vocal cords of the human body during vocalization, so as to evaluate the vocal cord ability without a professional teacher or professional equipment. In this system, we can use two wearable sensors, vibrating plate and headset, to collect the signals of the human vocal cords, or directly use the microphone of the mobile device to collect. And we use the convolutional neural network to analyze the signals and classify the closed state of the vocal cords. In order to build this system, we constructed a vowel data set classified by degree vocal cords closure, including the wearable sensors and mobile phone microphones we used. We compared the performance of the traditional vocalization pattern classification method and the convolutional neural network method we used to classify the vocal cord closure types on the data set we constructed and the public data set, and finally tested under two noise environments, and the preliminary results proved the usability of our system. © 2022, ICST Institute for computer sciences, Social Informatics and Telecommunications engineering.

关键词： Professional aspects

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Modif-SegUnet: Innovatively Advancing Liver Cancer Diagnosis and Treatment through Efficient and Meaningful Segmentation of 3D Medical Images

Modif-SegUnet: Innovatively Advancing Liver Cancer Diagnosis...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Wang, Chenhang Jin, Yujian Liang, Jiayi Yang, YuHan Nie, Shanling Hai, Yang East China University of Science and Technology Department of Computer Science and Engineering Shanghai China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai China The University of Sydney Faculty of Engineering Sydney Australia

ISBN: (纸本)9798350337488

Hepatocellular Carcinoma (HCC) holds a record of high incidence and severe global harm. In tasks of liver cancer segmentation based on 3D medical images, the majority of methods have endeavored to enhance the 3D U-net by integrating the latest modules from the field of computer Vision (such as the transformer), often overlooking the distinct characteristics of liver components. We introduced a novel deep learning architecture, Modif-SegUnet, to circumvent this limitation. This architecture extends the U-net model by incorporating a 3D-modifiable attention module, thereby fostering a heightened focus on distinguishing between normal liver sections and lesions. Furthermore, Modif-SegUnet ingeniously amalgamates the 3D-modifiable attention module with the Modif-transformer block, enabling efficient capture of relevant and valuable full-text information in CT images that contain liver or tumor regions. We subjected the proposed Modif-SegUnet to evaluation on the Liver Tumor Segmentation benchmark dataset. Experimental outcomes indicate that our methodology surpasses state-of-the-art approaches in liver tumor segmentation, suggesting potential pathways for advancing the diagnosis and treatment of liver cancer. © 2023 IEEE.

关键词： 3D medical image attention CT Liver cancer Segmentation transformer U-Net

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The Emergence of IIoT and its Cyber Security Issues in Critical Information Infrastructure 21

The Emergence of IIoT and its Cyber Security Issues in Criti...

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21st European Conference on Cyber Warfare and Security, ECCWS 2022

作者： Bhaiyat, Humairaa Yacoob Sithungu, Siphesihle Philezwini Academy of Computer Science and Software Engineering Faculty of Science University of Johannesburg South Africa

ISBN: (纸本)9781914587405

The emergence of the Industrial Internet of Things (IIoT) can transform and improve industrial domain processes. This is achieved by IIoT’s ability to collect and process vast amounts of data using technology such as sensors. IIoT capabilities can improve the manufacturing processes of these sectors and contribute to the improved functioning of critical information infrastructure. In addition, current trends - such as the Fourth Industrial Revolution (4IR) - use IIoT to realise specific goals. While the emergence of IIoT systems does introduce many benefits, such as improved efficiency and sustainability, it can also introduce security concerns. These security concerns pose a significant threat to the industrial domain, including critical information infrastructures. The resulting threats emphasise the need to implement solutions to secure IIoT systems. The paper aims to discuss the emergence of IIoT and its cyber security issues within the context of critical information infrastructure. The research paper follows a theoretical research methodology to provide an improved understanding of the emergence of IIoT and its cyber security issues in critical information infrastructure. The paper contains an exhaustive discussion of what is IIoT. A discussion on where IIoT fits within the context of critical information infrastructure and its impact on 4IR is also highlighted in the paper. Due to the many vulnerabilities that IIoT systems can contain, the paper also discusses security concerns surrounding the emergence of IIoT. The security concerns make IIoT systems attractive targets for cyberattacks. Therefore, different approaches that can be applied to secure IIoT systems is also provided. Since IIoT capabilities can impact the critical information infrastructure of businesses and nations, the authors’ stance on how IIoT systems could transform the current understanding of critical information infrastructure is also discussed. © 2022 Curran Associates Inc.. All rights r

关键词： Internet of things

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MFT: Modal Fusion Transformer for Cross-Modal Fusion in 3D Object Detection

MFT: Modal Fusion Transformer for Cross-Modal Fusion in 3D O...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Cai, Haojie Yin, Dongfu Yu, Fei Xiong, Siting Shenzhen University Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Shenzhen University Shenzhen China

ISBN: (纸本)9798350368741

Increasing attention has been garnered by LiDAR points and multi-view images fusion based on Transformer for supplementing another modality in 3D object detection. However, challenges persist for cross-modal fusion methods due to the heterogeneity of these two modalities, leading to issues such as inaccurate detection results encountered by Transformer-based methods. In this work, a one-way mid-level fusion based framework for 3D object detection named Modal Fusion Transformer (MFT) using LiDAR points and multi-view images is introduced. It comprises a Depth-Guided Generation(DGG) module, Position Encoding Generation (PEG) module and Cross Modal Fusion(CMF) module. Specifically, depth information from point cloud is utilized for both gathering the image depth map and initializing object queries in DGG. PEG unifies the form of position encoding from LiDAR features and multi-view image features. Depth and position information of object from images is aggregated to point clouds by CMF, which fully explores dual-modal information. Furthermore, a Modal Fusion Network with deformable attention named fast-MFT is introduced to reduce the relatively large computational cost associated with global attention. Our MFT and fast-MFT achieve competitive performance while maintaining a faster inference speed than other models. © 2025 IEEE.

关键词： 3D Object Detection Autonomous Driving Cross-Modal Transformer Positional Embedding Speed comparison

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Jaccard Index in Ensemble Image Segmentation: An Approach 5

Jaccard Index in Ensemble Image Segmentation: An Approach

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5th International Conference on Computational Intelligence and Intelligent Systems, CIIS 2022

作者： Ogwok, Daniel Ehlers, Elizabeth Marie Academy of Computer Science and Software Engineering University of Johannesburg South Africa

ISBN: (纸本)9781450397612

Many methods have been applied to image segmentation, including unsupervised, supervised, and even deep learning-based models. Semantic and instance segmentation are the two most widely researched forms of segmentation. It is of value to use multiple methods to segment an image. In this paper, we present an image segmentation ensemble methodology. Multiple image segmentation methods are applied to an image and merged to create one segmentation using the proposed method. The technique uses the Jaccard index algorithm, sometimes called the Jaccard similarity coefficient and commonly known as Intersection over Union (IoU). This resulted in better segmentation results than the respective individual segmentation methods. This experiment was applied to mathematical expression recognition (MER), with the expressions taken from blackboards with varying degrees of noise, and lighting conditions, from different classroom environments. A summary of empirical results from the segmentation of multiple images is presented in the paper. © 2022 ACM.

关键词： Semantics

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A Gene Expression Programming Inspired Evolution Symbiont Agent for Real-Time Strategy Generation 5

A Gene Expression Programming Inspired Evolution Symbiont Ag...

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5th International Conference on Computational Intelligence and Intelligent Systems, CIIS 2022

作者： Sithungu, Siphesihle P. Ehlers, Elizabeth M. Academy of Computer Science and Software Engineering University of Johannesburg South Africa

ISBN: (纸本)9781450397612

AdaptiveSGA is a method for achieving Adaptive Game Artificial Intelligence-Based Dynamic Difficulty Balancing through the Symbiotic Game Agent Model. Previous work has shown that AdaptiveSGA can achieve Dynamic Difficulty Balancing in simulated soccer by effectively changing a team's strategy based on the opponent's performance. AdaptiveSGA pre-existing strategies and switches between them during runtime to increase the game's replayability by adapting the challenge it poses to the human player. Although this method works, its limitation is that if the human player surpasses the most intelligent strategy of the computer opponent, there is no way for the model to generate a new strategy during runtime that can potentially overcome the human player. AdaptiveSGA can only maintain engagement with the human player if the human player has not overcome the best strategy for the pool of pre-existing strategies. Current work addresses this limitation by introducing an Evolution Symbiont Agent whose purpose is to generate new strategies in real-time (during gameplay) through evolutionary mechanisms using Gene Expression Programming. Experimental results show that the presence of the evolution symbiont agent can use Gene Expression Programming to generate strategies capable of outperforming an opposing strategy. © 2022 ACM.

关键词： Gene expression

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A Systematic Comparison between Flutter and React Native from Automation Testing Perspective 6

A Systematic Comparison between Flutter and React Native fro...

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6th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2022

作者： Zahra, Husam Abu Zein, Samer Birzeit University Department of Software Engineering and Computer Science Birzeit Palestine

ISBN: (数字)9781665470131

ISBN: (纸本)9781665470131

In recent years, mobile applications have attempted to significantly improve our lives. Android and iOS are the two most popular mobile platforms, yet they have varied settings (OS versions, screens, manufacturers, etc.) as a result creating a mobile application might be difficult. In recent years, several cross-platform frameworks, such as Flutter and React Native, have shown to be pioneers in this field. For developers, however, choosing cross-platform can be an intimidating task. In this research, we examine the automated testing capabilities of the Flutter and React Native frameworks in terms of automation testing. We concentrate on automation testing reusability, integration, and compatibility. We created a To-Do List mobile app in Flutter and React-Native by using *** as an automation testing platform. As a result of this research, the experiment demonstrates that React Native outperforms Flutter in terms of reusability and compatibility, with no significant difference in terms of integration, © 2022 IEEE.

关键词： Reusability

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