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8th International Conference on Advanced Computing and Communication Systems, ICACCS 2022

作者： Vasudeva, Kshitiza Biswas, Soumita Chandran, Saravanan National Institute of Technology Dept. Computer Science and Engineering Durgapur India Jalpaiguri Govt. Engineering College Dept. of Information Technology Jalpaiguri India

ISBN: (纸本)9781665408165

Experts can predict the state of mind from human facial expressions and can be used in various human-machine interaction applications. In such applications the countenance recognition plays a crucial role. Understanding of Human be-haviour, predicting Mental health, and recognizing fabricated human expressions are some of the several applications of Automatic facial expression recognition system. Though predicting a human expression is an easy task for humans but it invites a competitive research work for computers to recognize expressions efficiently by extracting facial features from a digital image. As per the literature the basic approach used by the researchers for the automatic facial expression recognition system are based on appearance and geometry. Several techniques have been proposed by researchers for the Facial Expression Recognition. These techniques can be put into two broad categories, Con-ventional and Deep Learning methods. In this research work, the conventional methods Local Binary Pattern (LBP), Principal Component Analysis (PCA), Random Forest, and Support Vector Classifier (SVC) models are studied and implemented. From Deep learning category, a CNN model is developed and tested on the dataset FER2013. All the models implemented, tested on the same dataset are put into comparison with some existing techniques. From the analysis it can be concluded that Deep learning techniques perform better. © 2022 IEEE.

关键词： Principal component analysis

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Geometric Reconstruction in Modern Remote Sensing Techniques and Applications 4

Geometric Reconstruction in Modern Remote Sensing Techniques...

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4th International Conference on Advancement in Electronics and Communication engineering, AECE 2024

作者： Temara, Sheetal Ravindran, Sindhu Sreevidya, Nelli Krishnmoorthi, Sathya Devarasu, Neelamegam Thota, Krishna Kishore University of the Cumberlands Department of Computer and Information Sciences United States Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Chennai India Sreenidhi Institute of Science and Technology Dept. of It Telangana Hyderabad India Kongu Engineering College Dept. of Artificial Intelligence TN Erode India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Dept. of Ece TN Chennai India AP Guntur India

ISBN: (纸本)9798350364729

This paper introduces a novel method for geometric reconstruction in remote sensing, combining LiDAR, SAR, deep lea0rning algorithms, and multi-sensor fusion. The proposed approach achieves a geometric reconstruction accuracy of 0.92, significantly higher than conventional methods, which average around 0.78. The method also reduces processing time to 28 seconds from the typical 45 seconds. By integrating LiDAR and SAR data, our approach enhances spatial feature extraction and reconstruction precision, making it highly effective for applications like urban planning, disaster response, and environmental monitoring. With an Intersection over Union (IoU) score of 0.88, the method demonstrates superior performance compared to traditional techniques. © 2024 IEEE.

关键词： Urban planning

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Third Generation Security System for Face Detection in ATM Machine Using computer Vision 1

Third Generation Security System for Face Detection in ATM M...

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1st International Conference on computer, Power and Communications, ICCPC 2022

作者： Sridevi, S. Monica, K.M. Senthil, G.A. Prabha, R. Sathya, A. Ramya, J. Sri Ramachandra Engineering and Technology Dept. of Computer Science and Engineering Chennai India Vit Chennai Campus Dept. of Computer Science and Engineering Chennai India Agni College of Technology Dept. of Information Technology Chennai India Sri Sai Ram Institute of Technology Dept. of Electronics and Communication Engineering Chennai India Sri Sai Ram Institute of Technology Dept. of Artificial Intelligence and Data Science Chennai India Dept. of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350397840

A workflow is proposed for the detection of unauthorized persons in an ATM. Certain assumptions, including the context of identification are made by training their features and storing the datasets. However, not every individual will be a suspect. Suspicious activity on ATMs that are located in remote areas and to reduce the risk of fraudulent transactions. such as using another person's card to withdraw money etc., Various video survey and image processing have been discussed in relation to surveillance methods. It discusses the various processes, preprocessing, classification, feature extraction and the corresponding video processing methods. © 2022 IEEE.

关键词： Face recognition

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Singer Separation for Karaoke Content Generation 27

Singer Separation for Karaoke Content Generation

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27th Conference on the Oriental COCOSDA International Committee for the Co-Ordination and Standardisation of Speech Databases and Assessment Techniques, O-COCOSDA 2024

作者： Lin, Hsuan-Yu Chen, Xuanjun Jang, Jyh-Shing Roger Graduate Institute of Networking and Multimedia National Taiwan University Taipei Taiwan Graduate Institute of Communication Engineering National Taiwan University Taipei Taiwan National Taiwan University Dept. of Computer Science and Information Engineering Taipei Taiwan

ISBN: (纸本)9798331506032

Due to the rapid development of deep learning, we can now successfully separate singing voice from mono audio music. However, this separation can only extract human voices from other musical instruments, which is undesirable for karaoke content generation applications that only require the separation of lead singers. For this karaoke application, we need to separate the music containing male and female duets into two vocals, or extract a single lead vocal from the music containing vocal harmony. For this reason, we propose in this article to use a singer separation system, which generates karaoke content for one or two separated lead singers. In particular, we introduced three models for the singer separation task and designed an automatic model selection scheme to distinguish how many lead singers are in the song. We also collected a large enough data set, MIR-SingerSeparation11, which has been publicly released to advance the frontier of this research. Our singer separation is most suitable for sentimental ballads and can be directly applied to karaoke content generation. As far as we know, this is the first singer-separation work for real-world karaoke applications. © 2024 IEEE.

关键词： Source separation

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Implementing Secure Key Management and Distribution in Cloud Environment 2

Implementing Secure Key Management and Distribution in Cloud...

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2nd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2023

作者： Lamsal, Aman Paul, Aniket Buchade, Amar Nalavade, Jagannath Bidwe, Ranjeet MIT Art Design and Technology University Dept. of Computer Science and Engineering Pune India Vishwakarma Institute of Information Technology Pune Savitribai Phule Pune University Pune India Department of Computer Engineering Pune India

ISBN: (纸本)9798350333763

Key management is considered as an essential aspect of securing cloud-based systems and data. As more organizations move their operations to cloud, the need for secure and efficient key management solutions becomes increasingly important. En-suring security of cloud computing is essential as many users often store their sensitive information with the cloud providers. Cloud service providers offer Key Management Services (KMS) to manage cryptographic keys for their customers, but there are still several challenges related to key management in cloud environments, including key storage, access control, and key rotation. Our research project aims to address these challenges by developing a secure and efficient key management solution for cloud-based systems. We propose a system that uses a combination of various cloud services and encryption algorithms to generate, store, and manage cryptographic keys securely. Our system provides granular access controls, and strong encryption to ensure the confidentiality and integrity of the keys. We believe that our proposed solution will help cloud service providers and organizations to manage their cryptographic keys more efficiently and securely, reducing the risk of unauthorized access and data breaches. This research paper provides a method to effectively manage, store and share the secret key between the parties using the concept of Threshold Cryptography. © 2023 IEEE.

关键词： Access control

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Differential Diagnosis of Lung Disease through Quantitative Lung Ultrasound Spectroscopy, an in vivo clinical study over 114 patients

Differential Diagnosis of Lung Disease through Quantitative ...

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2023 IEEE International Ultrasonics Symposium, IUS 2023

作者： Mento, Federico Perpenti, Mattia Barcellona, Giuliana Perrone, Tiziano Demi, Libertario Dept. of Information Engineering and Computer Science Ultrasound Laboratory Trento University of Trento Trento Italy Emergency and Urgency Department Humanitas Gavazzeni Bergamo Bergamo Italy

ISBN: (纸本)9798350346459

Lung ultrasound (LUS) represents an important imaging tool to evaluate the state of the lung surface. However, it is mainly based on the visual interpretation of imaging artifacts, especially the vertical ones. This subjective interpretation leads to poorly reproducible approaches, and, thus, qualitative diagnoses. Therefore, in this study, we present a quantitative multifrequency analysis based on the parameterization of vertical artifacts. Specifically, radiofrequency (RF) data were acquired from 114 patients affected by different diseases using a linear and a convex probe, connected to the ULtrasound Advanced Open Platform (ULA-OP). The vertical artifacts observed in patients affected by pneumonia, cardiogenic pulmonary edema (CPE), and pulmonary fibrosis (PF) were extracted and analyzed. Specifically, the significance of three features (native frequency, bandwidth, and total intensity) in discriminating these diseases was evaluated. The results show how the total intensity seems significant in differentiating PF from the other two diseases (p-value © 2023 IEEE.

关键词： Ultrasonics

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Monocular UAV Motion Planning Method Based on Deep Reinforcement Learning

Monocular UAV Motion Planning Method Based on Deep Reinforce...

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2025 IEEE International Conference on Consumer Electronics, ICCE 2025

作者： Hsueh, Man-Chen Ku, Chun Chen, Xiu-Zhi Chen, Yen-Lin Dept. of Computer Science & Information Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)9798331521165

This paper presents a monocular UAV motion planning method based on the DRL method SDDPG. By processing image data with the self-proposed lightweight dept. estimation model and a pretrained encoder, the information is sent into an improved Actor-Critic Network, which addresses overestimation issues and enhances learning efficiency. The experiments were conducted in Unreal Engine 4 and Airsim, which demonstrate the improvement of the motion planning ability, enabling UAVs to autonomously navigate and safely reach the defined destination. © 2025 IEEE.

关键词： Drones

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Monocular UAV Motion Planning Method Based on Deep Reinforcement Learning

Monocular UAV Motion Planning Method Based on Deep Reinforce...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Man-Chen Hsueh Chun Ku Xiu-Zhi Chen Yen-Lin Chen Dept. of Computer Science & Information Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

关键词： Visualization Image coding Navigation Computational modeling Atmospheric modeling Network architecture Autonomous aerial vehicles Deep reinforcement learning Planning Resource management

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A Graph Convolutional Attention Network with Q-net on Multi-agent Systems 2

A Graph Convolutional Attention Network with Q-net on Multi-...

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2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing, AIAHPC 2022

作者： Li, Yupei Shen, Tianqi Liu, Zhiyuan Dept. of Computer Science University of Oxford Oxford United Kingdom Department of AeroSpace Information Engineering Beihang University Beijing China Dept. of Computer Science University of Toronto TorontoON Canada

ISBN: (纸本)9781510657717

In recent years, GNNs have becoming one of the hottest topics of deep learning due to their powerful ability in modeling relational data and their wide applications in real world. Besides, reinforcement learning is widely applied in many fields. However, the tradition way to train the reinforcement learning is not that accurate enough. It can be assumed that it is wise to combine GNN and reinforcement learning, making good use of the modeling capability of GNNs, to enhance the reinforcement learning performance. In this paper, the most ordinary GNN is compared within the existing works to see whether it is possible to combine GNN and reinforcement learning. PettingZoo is chosen on behalf of the multi-agent system, and a Graph Convolutional Attention Network with Q-net (GCANQ) is designed and validated, which shows the efficient computational capability of GNN. Experiments show that GNN performs strikingly well on a common multiagent system and in a small scale with some overfit as well. Moreover, the speed of the training of GCANQ is acceptable for the complex calculation needed. © 2022 SPIE. All rights reserved.

关键词： Graph neural networks

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Reliability Measures in Neutrosophic Soft Graphs

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Neutrosophic Sets and Systems 2022年 49卷 239-252页

作者： Anirudh, A. Kannan, R. Aravind Sriganesh, R. Sundareswaran, R. Kumar, S. Sampath Shanmugapriya, M. Broumi, Said Dept. of Computer Science Sri Sivasubramaniya Nadar College of Engineering India Dept. of Electrical and Electronics Engineering. Sri Sivasubramaniya Nadar College of Engineering India Dept. of Mathematics Sri Sivasubramaniya Nadar College of Engineering India Laboratory of Information Processing Faculty of Science Ben M'Sik University Hassan II B.P 7955 Sidi Othman Casablanca Morocco

This paper introduces the concept of reliable nodes in neutrosophic soft graphs by evaluating path-based parameters. A reliable node is defined as one which is least susceptible to changes that are quantized by the indeterminacy and falsity values in a neutrosophic tuple. A new path measure called farness and three novel reliability measures which make use of the same are presented. Farness is defined in terms of a novel score function. The first, proximity reliability of a node, computes the farness of a node to its neighbours. The second, intermediate reliability of a node, computes the fraction of paths of minimal farness that pass through it. The third, crisis reliability of a node, is a hybrid of the two previously defined. It considers the farness of a node to its neighbours taking into account the farness of the neighbours to other nodes in the graph. © 2022. All Rights Reserved.

关键词： Reliability

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