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Video Arbitrary Style Transfer via Style Attention and Contrastive Learning 5

Video Arbitrary Style Transfer via Style Attention and Contr...

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5th International conference on High Performance Big Data and Intelligent systems, HDIS 2023

作者： Qian, Yangyang Qin, Wei Pei, Songwen Tan, Junhao School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai China

ISBN: (纸本)9798350394160

With the development of Generative AI technologies, video style transfer has become a popular extra challenge of style transfer. Compared to traditional images style transfer tasks, video tasks bring new challenges in maintaining temporal consistency and desirable stylized results. To solve the problem, we proposed a two-stage network combining Style Attention and Contrast learning(SACNet). Specifically, in the first stage, we proposed an adaptive filter incorporating attention mechanism to deal with texture artifacts and edge artifacts. the filter adjusts the features both inner channels and inter channels. In the second stage, we proposed a Temporal-consistency Contrastive Loss Module(TCLM) to solve the problems of stability and flicker artifacts for stylized videos. the TCLM is defined by single-frame local patches with looser constraints. In addition, color loss function was introduced to adjust the stylized color saturation. In contrast to the current SOTA models for video style transfer, SACNet achieved an average LPIPS by 0.152 and a temporal-consistency loss by 0.034 on the MPI-Sintel dataset, it respectively achieved reductions by 5% and 20% on average. It was verified that SACNet could perform well in various style transfer tasks for images and videos. ©2023 IEEE.

关键词： Adaptive filters

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Ensemble Learning for Offline Signature Verification using Fused Deep Features

Ensemble Learning for Offline Signature Verification using F...

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International conference on Advancements in Computational Sciences (ICACS)

作者： Sara Tehsin Ali Hassan Farhan Riaz Department of Computer and Software Engineering NUST Islamabad Pakistan Deparment of Computer Engineering HITEC university Taxila

Signature verification plays an important role in document authentication. the efficient and robust system is required for forgery detection in documents in the presence of distortion such as rotation, scaling and noise. this paper proposes a writer-dependent signature verification method, where hand-crafted features are fused with one-dimensional convolutional neural network features to cater different variance in the whole verification process. Proposed feature extraction methodology is validated by bagged ensemble learning technique in which machine learning classifier’s decision is finalized based on majority voting. the effectiveness of the proposed signature verification approach has been evaluated across three distinct publicly accessible datasets. the outcomes highlight the versatility of this method. Moreover, the proposed system surpasses the performance of other pre-existing systems documented in the literature.

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Innovation Approaches in CAD systems Training Program

Innovation Approaches in CAD Systems Training Program

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Electronic engineering, Information Technology & Education (EEITE), International conference in

作者： Volodymyr Shanaida Valeriy Lazaryuk Andrii Blavitskyi Justyna Żylińska Stanisłw Tkaczyk Volodymyr Hutsaylyuk Design of Machine Tools Instruments and Machines Department Ternopil Ivan Puluj National Technical University Ternopil Ternopil Ukraine Department of Mechanical Engineering Technology Ternopil Ivan Puluj National Technical University Ternopil Ukraine Department Automation and Computer integrated Technologies Ternopil Ivan Puluj NationalTechnical University Ternopil Ternopil Ukraine Faculty of Management and Logistics Helena Chodkowska University of Technology and Economics Warsaw Poland Faculty of Engineering Helena Chodkowska University of Technology and Economics Warsaw Warsaw Poland

ISBN: (数字)9798350372878

ISBN: (纸本)9798350372885

the advancements in information technology and computer-aided design have paved the way for virtual modeling and exploration of real-life objects. In the realm of CAD systems, there are subgroups of specialized software (CADCAM- CAE systems) that are designed to accomplish specific object-oriented tasks. Such software is primarily used for mathematical computations, analytic studies of schematic technical objects, and 2D and 3D systems for engineering design practices.

关键词： Training Technological innovation Solid modeling three-dimensional displays Object oriented modeling software algorithms Solids

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FCMCP: Fuzzy C-Means for Controller Placement in software Defined Networking

FCMCP: Fuzzy C-Means for Controller Placement in Software De...

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13th International conference on Ambient systems, Networks and Technologies, ANT 2022 / 5th International conference on Emerging Data and Industry 4.0, EDI40 2022

作者： thalapala, Vidya Sagar Guravaiah, Koppala Department of Computer Science and Engineering Indian Institute of Information Technology Kottayam Kerala686635 India

One of the most critical factors in SDN networks is the controller placement. the controller's location determines the network delay. Reduction in network latency can help to scale the network effectively. A Fuzzy C-Means approach is used for placement of controller in optimized manner to improve the network latency. A topology-zoo network data-set, such as OS3E and Chinanet, were used to validate the proposed FCMCP. this technique offers faster response time than K-Clustering methods such as K-Center, K-Mean, etc. Finally, the Fuzzy C-Means method reduces latency by 18% when compared to the K-Clustering methods. © 2022 Elsevier B.V.. All rights reserved.

关键词： Controller Placement Problem FCM FCMCP Fuzzy C-Means Internet Topology Zoo Latency Multi-Controller Scalability software Defined Networking

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Heterogeneous Computing and Applications in Deep Learning: A Survey 22

Heterogeneous Computing and Applications in Deep Learning: A...

引用

5th International conference on computer Science and software engineering, CSSE 2022

作者： Wu, Qiong Shen, Yuefeng Zhang, Mingqing Beijing Institute of Computer Technology and Application China

ISBN: (纸本)9781450397780

With the rapid development of deep learning, a variety of neural network models emerge in endlessly, which leads to a huge demand for computing resources. For the intensive numerical computation of neural networks, various computing devices represented by GPUs are favored by researchers. Heterogeneous computing is a kind of technology that can integrate a variety of computing devices with different architectures, and it will be further developed. therefore, this paper reviews research on some key technologies of heterogeneous computing, including the architecture of heterogeneous computing, the programming language of heterogeneous computing, and the scheduling algorithm for heterogeneous systems. then, we focus on the research of heterogeneous computing in deep learning, including the parallel technology of neural networks and optimization technology based on heterogeneous systems. Finally, the present research situation is discussed and analyzed, and the future research direction is prospected, aiming to provide some basis for related research. © 2022 ACM.

关键词： Network architecture

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Control Strategy Based on Vision for Security in Communication systems 5

Control Strategy Based on Vision for Security in Communicati...

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5th IEEE International conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Bhati, Sunita Bhati, Anita Shah, Bharti Pachauri, Divya Alleema, N.Noor Patel, Mayank Jecrc University Jaipur India Jaipur National University Jaipur India Gls University Faculty of Computer Applications & It Ahmedabad India Nitra Technical Campus Ghaziabad India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Chennai India Geetanjali Institute of Technical Studies Udaipur India

ISBN: (纸本)9798350383522

Forests are crucially important to maintaining ecological balance and providing all essential life services. Still, the constant protection against illegal, destructive exploitation is a difficult challenge that many people do not think about. - To address this issue, a new camera-based access control system for entry and exit to the protected forest areas that minimizes the number of people with insider knowledge is used for. Unauthorized access to sensitive or restricted areas is eliminated. - In an increasingly vulnerable world where greedy exploitation and human invaders abound, it has now become an urgent need to look after forests. To protect protected forest areas against such threats as loss of habitat, illegal logging, and poaching and the damage done to ecosystems (once their borders are crossed), one must rely on stringent security measures. - Traditional forest preservation strategies lack comprehensive monitoring and access control. But that's why security and refurbishment of forests are such pressing issues now-and why this project is so vital. - Our system aspires to provide real-time surveillance, access control, and automated alerts if any unauthorized human activity occurs within protected forest areas;for this we need cutting edge hardware and software technologies. the main goal is to create a secure, reliable, efficient access control system for protected forest areas, which presents special problems. - the System will use a camera and software on the basis of the ESP32 to capture and analyze images for identity verification. Unauthorized individuals trying to gain entry will trigger an alert for subsequent investigation or logging. - the study of the camera-based access control system covers the design, installation and testing as well as its operation. this includes hardware/software components and system architecture, which integrates with the Blynk cloud-based server to provide data storage and analytics. - Emphasis: there should be a conce

关键词： alert and notification cloud flood monitoring iot

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Visual object detection using audio data 5

Visual object detection using audio data

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5th International conference on Computing and Data Science, CONF-CDS 2023

作者： Chaturvedi, Rajnish Kumar Sahu, Dinesh Prasad Tyagi, Manoj Kumar Diwakar, Manoj Singh, Prabhishek Shankar, Achyut Sathishkumar, V.E. Schoolof Computer Science Engineering and Technology Bennett University Greater Noida India Galgotias University India CSE Dept. Graphic Era Deemed to Be University Dehradun India University of Warwick United Kingdom Department of Software Engineering Jeonbuk National University Jeonju-si Jeollabuk-do Korea Republic of

Nowadays Internet of things (IoT) and Machine Learning (ML) are growing fields. One application of these two fields is object detection, which detects semantic objects using digital images and videos of classes like humans, vehicles, buildings, etc. Visual object detection systems are very effective and accurate due to the appearance information obtained from the cameras. But they face the problem of a limited Field of View. this paper aims to tackle this issue by using audio data to localize the object. A microphone is used to estimate the angular position of the object emitting the sound. Objects currently in the Field of View of a camera are detected and tracked using optical flow, but when they go out of the Field of View, the sound emitted by the object is used by the microphone to calculate the object's angular position. Once the angle is calculated, the camera is rotated in that direction. this thus ensures that the object can be located even if it goes out of frame. Once the object is located through IoT devices, we use ML to identify the person's face. © Published under licence by IOP Publishing Ltd.

关键词： Object detection

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Heterogeneous Statistical QoS Provisioning for Scalable software-Defined 6G Mobile Networks 57

Heterogeneous Statistical QoS Provisioning for Scalable Soft...

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57th Annual conference on Information Sciences and systems, CISS 2023

作者： Zhang, Xi Zhu, Qixuan Poor, H. Vincent Texas AandM University Networking and Information Systems Laboratory Department of Electrical and Computer Engineering College StationTX77843 United States Princeton University Department of Electrical and Computer Engineering PrincetonNJ08544 United States

ISBN: (纸本)9781665451819

Due to the explosively increasing number of mobile users and the new types of data demands in the fifth generation (5G) mobile wireless network, research in wireless networks has shifted toward the development of the sixth-generation (6G) wireless network. Although the research for software-defined network (SDN) architectures in 5G mainly focuses on the dynamic programming for the internet backbone, these software programming techniques can be also applied at the network edge to support the exponentially increasing demands from mobile users under constrained wireless resources. In order to study the interference problem resulted by massive mobile users, the scaling law is a powerful tool to show how fast the levels of network imperfections can be tolerated as the number of mobile users increases. In this paper, we investigate the scaling behavior of software-defined architectures over 6G wireless networks. We consider the wireless channel in three scenarios: single-input-single-output (SISO), multiple-input-single-output (MISO), and multiple-input-multiple-output (MIMO), where we derive the corresponding scaling law for each scenario, respectively. Our derived scaling law shows how the network performance scales with the number of mobile users in a wireless network. then, we propose a software-defined network slicing scheme to select the optimal mobile users and derive their optimal resource allocations, according to our derived scaling law, under SISO, MISO, and MIMO wireless channel, respectively. Finally, we validate and evaluate the derived scaling behavior of the software-defined architecture over 6G wireless networks through numerical analyses. © 2023 IEEE.

关键词： Wireless networks

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A Review for Managing Data Integrity in Multi-Tenant Based Cloud systems 5

A Review for Managing Data Integrity in Multi-Tenant Based C...

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5th International conference on Contemporary Computing and Informatics, IC3I 2022

作者： Dheeraj, Nikkondi Kaur, Manjot Lovely Professional University School of Computer Science Engineering Jalandhar India

ISBN: (纸本)9798350398267

Cloud is a vast and ever-growing technology in the world which is primarily used for data sharing and resource sharing purposes. By benefitting this technology there are many service providers who are providing SAAS architecture. An SAAS providing company can provide security in its database but while we are connecting with remote site, we cannot tell which sites are to be trusted. While using this architecture the data must be passed through different set of nodes as it is wireless architecture which gives the chance to attackers to sniff the data while transferring the data from source to destination. there are many attacks exploiting this type of services one of the most notorious attack methods is salami attack. To prevent this type of attacks we can third party auditing which helps in protecting the data from unauthorized personnel. © 2022 IEEE.

关键词： software as a service (SaaS)

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An FPGA-based Fall Detection System Using Millimeter-wave Radar and Convolutional Neural Network 5

An FPGA-based Fall Detection System Using Millimeter-wave Ra...

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5th IEEE International conference on Electronic Information and Communication Technology, ICEICT 2022

作者： Cao, Jun Feng, An Kang Wang, Bo Research Institute Department of Communication Engineering Nanjing China Research Institute Department of Electrical and Computer Engineering Suzhou China

ISBN: (数字)9781665472111

ISBN: (纸本)9781665472111

Falls have become the second leading cause of unintentional injury death in the elderly. Timely detection of falls in the elderly can avoid greater injuries. therefore, it is increasingly important to study fall detection systems. Based on this background, a fall detection system is designed in this paper. A fall detection system is usually divided into two parts: data acquisition and feature recognition. Due to its excellent confidentiality and applicability, millimeter-wave radar is used for data acquisition in this paper. Usually, the data collected by millimeter-wave radar is processed in a computer, and feedback is given to fall or not. But the data processing software in the computer brings great convenience to the system at the same time, it also limits the stability and portability of the system and hinders the practical application of the system. For this, the system introduces FPGA (Field Programmable Gate Array) to replace the computer for all the data processing including short-time Fourier transform and CNN (Convolutional Neural Network) feature recognition. Experimental results show that the system can detect falls accurately in simple cases, which preliminarily proved the feasibility of FPGA application in the fall detection system. the FPGA-based fall detection system can realize miniaturization and low price through tape-out after further improvement, and promote the practical application of the fall detection system. © 2022 IEEE.

关键词： Fall detection

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