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GAN-Based Multi-Decomposition Photo Cartoonization

GAN-Based Multi-Decomposition Photo Cartoonization

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作者： Zhao, Wenqing Zhu, Jianlin Huang, Jin Li, Ping Sheng, Bin School of Computer Science and Artificial Intelligence Wuhan Textile University Wuhan China Department of Computer Science South-central Minzu University Wuhan China Department of Computing and The School of Design The Hong Kong Polytechnic University Hong Kong Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

Background: Cartoon images play a vital role in film production, scientific and educational animation, video games, and other fields, and are one of the key visual expressions of artistic creation. However, since hand-crafted cartoon images often require a great deal of time and effort on the part of professional artists, it is necessary to be able to automatically transform real-world images into different styles of cartoon images. Although cartoon images vary from artist to artist, cartoon images generally have the unique characteristics of being highly simplified and abstract, with clear edges, smooth color shading, and relatively simple textures. However, existing image cartoonization methods tend to create a number of problems when performing style transfer, which mainly include: (1) the resulting generated images do not have obvious cartoon-style textures;and (2) the generated images are prone to structural confusion, color artifacts, and loss of the original image content. Therefore, it is also a great challenge in the field of image cartoonization to be able to make a good balance between style transfer and content keeping. Methods: In this paper, we propose a GAN-based multi-attention mechanism for image cartoonization to address the above issues. The method combines the residual block used to extract deep network features in the generator with the attention mechanism, and further strengthens the perceptual ability of the generative model to cartoon images through the adaptive feature correction of the attention module to improve the cartoon features of the generated images. At the same time, we also introduce the attention mechanism in the convolution block of the discriminator, which is used to further reduce the image visual quality problem caused by the style transfer process. By introducing the attention mechanism into the generator and discriminator models of the generative adversarial network, our method enables the generated images to have obvious c

关键词： Generative adversarial networks

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Coverage Hole Aware Data Routing for Mobile Sink Wireless Sensor Networks 14

Coverage Hole Aware Data Routing for Mobile Sink Wireless Se...

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14th IEEE International Conference on Electronics Information and Emergency Communication, ICEIEC 2024

作者： Wedaj, Fisseha Teju Hawbani, Ammar Wang, Xingfu Al-Gunid, Haithm M. Yilma, Getinet Farooq Qaisar, Muhammad Umar University of Science and Technology of China School of Computer Science and Technology Hefei China Shenyang Aerospace University School of Computer Science Shenyang China Adama Science and Technology University School of Electrical Engineering and Computing Adama Ethiopia Southern University of Science and Technology School of System Design and Intelligent Manufacturing Shenzhen China

ISBN: (纸本)9798350361889

In wireless sensor networks (WSNs), the coverage hole problem is one of the challenging problems that needs an effective solution. Data routing protocols in WSNs aim to disseminate the sensors' data to the central device with the minimum possible network resource usage. However, suppose there is a coverage hole in the middle of the source and destination nodes, and the source node doesn't have information about the hole. In that case, the data may choose the longer and more repetitive path to reach the destination, increasing resource usage, mainly energy and time. The condition is even more challenging when the network employs a mobile data collector. This paper proposes a Coverage Hole Aware Data Routing (CHADR) protocol for Mobile Sink WSNs that determines the shorter hole bypassing path in advance at the source node using the hole and data collector location information. CHADR evaluates the path efficiency using directional angle and expected hops count. After determining the path, data will be transmitted to the mobile sink using an Opportunistic routing technique. We proved CHADR performance with experimental simulations. © 2024 IEEE.

关键词： Routing protocols

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Data Analytics Using Machine Learning for Cyber Security Safeguards Individual Privacy

Data Analytics Using Machine Learning for Cyber Security Saf...

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2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2023

作者： Sruthy, S. Ravindran, Zina Akhilkk Gouri, M.S. Waheeduddin Hussain, Mohammed Jothikumar, R. Kerala Palai India Baselios Mathews II College of Engineering Department of Computer Science and Artificial Intelligence Engineering Sasthamcotta690520 India Vimal Jyothi Engineering College Department of Computer Science and Design Chemperi India Baselios Mathews II College of Engineering Lake View Department of Computer Science and Engineering Kerala India Shadan College of Engineering and Technology Department of Information Technology Peerancheru Hyderabad India Shadan College of Engineering and Technology Department of Computer Science and Engineering Peerancheru Hyderabad India

ISBN: (纸本)9798350319200

The merging of data analytics and machine learning offers tremendous potential for boosting cyber security and protecting individual privacy in an age when personal data and cyber dangers are abundant. The purpose of this study was to create, test, and publish a model that takes into account this junction. Accuracy, precision, recall, F1-Score, and area under the receiver operating characteristic curve (AUC-ROC) are only a few of the indicators that show how well the framework can identify cyber threats. Further, the use of privacy-preserving methods like differential privacy highlights the moral need to guard sensitive information. Readers are given a concrete knowledge of the framework's real-world effect via vivid depictions of its practical use based on hypothetical data sets. This study serves as a helpful resource for a varied audience, from consumers worried about data privacy to organisations looking to better their cyber security defenses and legislators aiming to safeguard citizens' data. It also provides a springboard for further study in areas such as privacy enhancement, more sophisticated machine learning models, and sector-specific framework development. The digital ecosystem is always changing, but this study provides a guide for overcoming obstacles and capitalizing on possibilities at the intersection of cyber security and personal privacy. © 2023 IEEE.

关键词： Cyber Security Cyber Threat Detection Data Analytics Differential Privacy Digital Privacy Framework Development Individual Privacy Performance Metrics Privacy-Preserving Techniques User-Centric Security

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UAV-Assisted Data Synchronization for Digital-Twin-Enabled Vehicular Networks

UAV-Assisted Data Synchronization for Digital-Twin-Enabled V...

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2023 IEEE/CIC International Conference on Communications in China, ICCC 2023

作者： Wu, Guoquan Nie, Jiangtian Tang, Jianhang Zhang, Yang Xiao, Jiang Xiong, Zehui Yanshan University School of Information Science and Engineering China Nanyang Technological University School of Computer Science and Engineering Singapore Guizhou University State Key Laboratory of Public Big Data China Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology China Huazhong University of Science and Technology School of Computer Science and Technology China Singapore University of Technology and Design Pillar of Information Systems Technology and Design Singapore

ISBN: (纸本)9798350345384

Digital twin (DT) is becoming a promising solution for vehicular networks to improve the interoperability of distributed autonomous driving systems. Mobile edge computing (MEC) has been introduced to provide low-latency services for DT-enabled vehicular networks at the edge of the network. However, it is hard to obtain the dynamic network topology for moving vehicles by the ground-based MEC system, which may deteriorate the service quality for DT synchronization. In this paper, we propose a novel unmanned aerial vehicle (UAV)-assisted synchronization framework for DT-enabled vehicular networks. With the proposed framework, an intelligent resource allocation algorithm is developed to improve UAV resource utilization and maximize the synchronization completion ratio. By leveraging an advantage actor-critic (A2C) algorithm, the synchronization decisions are obtained with low time complexity. Experiment results demonstrate that the proposed algorithm can reduce the synchronization latency and improve the synchronization completion ratio effectively. © 2023 IEEE.

关键词： Resource allocation

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Attention Enhanced Feature Fusion for Mental Stress Level Classification 21

Attention Enhanced Feature Fusion for Mental Stress Level Cl...

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21st International computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2024

作者： Sahlu, Ameneshewa Abush Yohannes, Gobena Mulugeta Dawit, Bekalu Nigus Teshome, Molla Woretaw School of Computer Science and Engineering University of Electronic Science and Technology of China Sichuan Chengdu China School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China School of Information and Software Engineering University of Electronic Science and Technology of China Sichuan Chengdu China

ISBN: (纸本)9798331519254

Mental stress poses significant health risks, manifesting in various psychological and physical issues such as depression, anxiety, and cardiovascular complications. Establishing a reliable method for swiftly and accurately classifying mental stress levels is crucial due to its widespread impact. Existing classification approaches predominantly rely on either data-intensive traditional machine learning algorithms or opaque deep learning models, hindering real-world use and interpretability. This study addresses these limitations by proposing a novel approach for stress level classification using the WESAD dataset. Our method combines an attention-based ResN et with CBAM. This innovative approach synergistically integrates shallow and deep features, harnessing both low-level details and high-level semantic information to effectively classify stress levels into four distinct states: baseline, stress, amusement, and meditation, or three states excluding the meditation state. The experimental result shows 92.74% accuracy and 91.19% F1 score for the 4-class setup, and 97.58% accuracy and 97.51 % F1 score for the 3-class setup. Our approach offers a more robust and interpretable framework for mental stress classification, with potential applications in health care and stress management. © 2024 IEEE.

关键词： Deep learning

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Optimizing AODV Routing Protocol to Improve Quality of Service Performance for V2V Communication

Optimizing AODV Routing Protocol to Improve Quality of Servi...

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2024 International Conference on Smart Computing, IoT and Machine Learning, SIML 2024

作者： Bintoro, Ketut Bayu Yogha Priyambodo, Tri Kuntoro Musthofa, Muhammad Nurul Gadjah Mada University Faculty of Mathematics and Computer Sciences Dept.of Computer Science and Electronics Yogyakarta Indonesia Universitas Trilogi Faculty of Sciences Technology and Design Dept. of Informatic Engineering Jakarta Indonesia

ISBN: (纸本)9798350364101

The study focuses on Quality of Service (QoS) issues in learning automata-based AODV (LA-AODV) for V2V communication protocols. It analyzes and compares the LAAODV protocol with the original AODV protocol in dynamic traffic situations. The study evaluates critical metrics such as the number of vehicles, average speed, congestion spots, and vehicle time loss across various traffic scenarios, including smooth traffic, steady flow traffic, and heavy traffic. NS3 and SUMO are used as essential tools for this evaluation. The study finds that the LA-AODV protocol performs better in smooth traffic conditions than AODV. It demonstrates a 38.27% higher packet delivery ratio (PDR), an 85.26% lower packet loss ratio (PLR), and a remarkable 56.62% increase in average throughput compared to AODV. Both protocols exhibit similar performance in steady flow traffic with high PDRs (97.60% and 96.87%, respectively) and low PLRs (2% and 3%, respectively). However, AODV outshines LA-AODV with a higher PDR (97.60%)) than LA-AODV (96.87%) in heavy traffic. LA-AODV, on the other hand, excels in average throughput by 17.24% in heavy traffic. The study offers valuable insights for improving V2V communication protocols and enhancing communication efficiency to handle dynamic and traffic situations. © 2024 IEEE.

关键词： Quality of service

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Role of IoT in Smart Cities: A Review, Applications, Open Challenges and Solutions 3

Role of IoT in Smart Cities: A Review, Applications, Open Ch...

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3rd International Conference on Electronics and Renewable Systems, ICEARS 2025

作者： Vivek, Kolla Swetha, Gurrala Kumar M, V. T. Ram Pavan Veni, Anusuri Krishna Praveen, Neti Kale, Masthan Rao Dept. of Cse Andhra Pradesh Ongole India Dept. of Cse Telangana India Kakaraparti Bhavanarayana College Dept. of Computer Science Andhra Pradesh Vijayawada India Madanapalle Institute of Technology & Science Dept. of Computer Science & Engineering - Data Science Andhra Pradesh Madanapalle517325 India Srkr Engineering College Dept. of Computer Science and Design Andhra Pradesh Bhimavaram India Dept. of Cse Andhra Pradesh Ongole India

ISBN: (纸本)9798331509675

Smart cities have emerged as a response to the fast expansion of metropolitan areas;these places strive to improve the lives of their residents while simultaneously promoting environmentally responsible growth. To maximize urban services, the Internet of Things (IoT) is an essential technology that allows for the seamless integration of sensors, devices, and systems. This allows smart cities to become a reality. With an emphasis on smart transportation, energy management, healthcare, environmental monitoring, and public safety, this paper explores the critical role of IoT in smart cities. Data security, privacy, scalability, and interoperability are some of the problems that arise when smart cities use IoT, despite the revolutionary potential it has. These obstacles are thoroughly examined in this work, along with possible solutions to these problems. This study gives a thorough overview of the IoT and its impact on smart city development, innovation, and urban resilience by focusing on the present situation, applications, and unanswered questions. © 2025 IEEE.

关键词： Digital Technology Drainage Monitoring Fire detection Smart City Waste Management

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Revolutionizing the Driving Experience : Enhancing Safety and Comfort Using ADAS 7

Revolutionizing the Driving Experience : Enhancing Safety an...

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2023 7th International Conference On Computing, Communication, Control And Automation, ICCUBEA 2023

作者： Kelkar, Aditya Jondhale, Digvijay Borade, Rugved Juneja, Ishan Haran, Yuvraj Pawar, Rajendra G. School of Computer Engineering & Technology Mit World Peace University Maharashtra Pune India Mit School of Computing Mit Art Design and Technology University Department of Computer Science Engineering Pune India

ISBN: (纸本)9798350304268

Advanced Driver Assistance Systems, or ADAS for short, are a group of technologies intended to help drivers operate their automobiles more safely and effectively. These systems often employ sensors, cameras, and other gadgets to keep an eye on the surroundings of the car and give the driver alerts or help in a multitude of circumstances, like lane departure, accident avoidance, and parking. Modern vehicles are increasingly utilizing ADAS technologies, which are regarded as an important first step towards completely autonomous vehicles. © 2023 IEEE.

关键词： ADAS Haar Cascade Object-detection RaspberryPi YOLO

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Review of Reinforcement Learning in Chrome Dino Game 7

Review of Reinforcement Learning in Chrome Dino Game

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2023 7th International Conference On Computing, Communication, Control And Automation, ICCUBEA 2023

作者： Kulkarni, Advait Bapat, Pranav Kulkarni, Tanvi Pawar, Rajendra School of Computer Engineering & Technology Mit World Peace University Maharashtra Pune India Mit School of Computing Mit Art Design & Technology University Department of Computer Science Engineering Pune India

ISBN: (纸本)9798350304268

The intention of this study is to study some implementation of reinforcement learning in the environment of Google Chrome's Dino Game. Different environments were tested on Deep Q network and proximal policy optimization models. Images were provided as inputs in all trials and the highest scores were recorded and analysed to check which algorithm and environment performed better. Further work aims at including more environments and algorithms and performing training on High performance computers. © 2023 IEEE.

关键词： Deep Q network OpenAI gym Proximal Policy Optimisation Reinforcement learning Selenium

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HAD B+-Tree: A Hotness-Aware Adaptive B+-Tree for SSD/HDD-Based Hybrid Storage Architecture 2

HAD B+-Tree: A Hotness-Aware Adaptive B+-Tree for SSD/HDD-Ba...

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2nd International Conference on Sensing, Measurement, Communication and Internet of Things Technologies, SMC-IoT 2023

作者： Wei, Yufei Du, Hui Jin, Peiquan University of Science and Technology of China School of Computer Science and Technology Hefei China Cnnc Huawei Engineering Design & Research Co. Ltd Nanjing China

ISBN: (纸本)9798350373257

Modern database systems have widely used B+-tree to index data. However, the traditional B+-tree will index all the keys within the dataset, yielding a large index size on big datasets. We note skewed query workloads are common in real applications, focusing on a small portion of the dataset. To this end, indexing the whole dataset is not necessary. Motivated by such an observation, we propose a new hotness-aware adaptive index called HAD B+-tree, which includes a hot B+-tree and a warm B+-tree on SSD and a full B+-tree on HDD. The hot and warm B+-trees index the keys that are frequently queried. The full B+-tree is stored on HDD to reduce storage costs. We maintain the hotness of keys through a heat-tracking table to determine which keys need to be indexed on the hot or warm tree. With such a mechanism, we demonstrate that search efficiency can be improved by controlling the height of the trees. We conduct experiments on real devices to compare the HAD B+-tree with the ordinary B+-tree and the adaptive merging under the YCSB workloads. The results suggest the efficiency and effectiveness of the HAD B+-tree. © 2023 IEEE.

关键词： Efficiency

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