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检索条件"任意字段=2022 3rd International Conference on Signal Processing and Computer Science, SPCS 2022"

共 761 条记录，以下是601-610 订阅

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Feature Extraction and Fusion of Multiple Convolutional Neural Networks for Firearm Detection 3rd

Feature Extraction and Fusion of Multiple Convolutional Neur...

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3rd international conference on Machine Intelligence and signal processing, MISP 2021

作者： Dhillon, Anamika Verma, Gyanendra K. Department of Computer Engineering NIT Kurukshetra Kurukshetra India

ISBN: (纸本)9789811908392

In the last few years, terror activities across the world have been raised drastically. Therefore, we need a framework that can detect these terror and illegal actions automatically. In spite of various state-of-the-art deep learning algorithms, weapon detection is still a serious challenge. This work focuses on the classification and detection of guns which integrates deep fusion of feature information to generate the most discriminant feature vector. Firstly, we utilize the fully connected layers of recent deep CNN models: Inception-ResNetv2 and MobileNetv2 for feature extraction, and then we fuse these features by using concatenation operation. To acquire a more compact presentation of features and reduce the complexity of computation, we have utilized NCA. After that, we classify the images by using an SVM classifier. Finally, to detect the guns in an image, a bounding box regression module is proposed by applying LSTM. Qualitative and quantitative outcomes indicate that our framework can detect guns with huge variations in size along with rigorous occlusion. In particular, our method achieves an accuracy rate of 98.62% with a false alarm rate of 1.38% on the gun dataset which is extracted from Kaggle. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Feature extraction

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Research on Chinese word sense disambigution based on Prompt learning

Research on Chinese word sense disambigution based on Prompt...

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computer science and Management Technology (ICCSMT), international conference on

作者： Ling Gan Xinrui Du School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China

Word sense disambiguation is an important research topic in natural language processing. Its purpose is to determine the word meaning of a polysemous word in different contexts. In order to improve the efficiency of disambiguation, a Chinese word sense disambiguation model PL-WSD based on prompt learning is proposed. The model uses the knowledge base HowNet to obtain the representation of each word meaning in polysemous words, uses the way of prompt learning to calculate the similarity score of each word meaning in a specific context, and obtains the word meaning with the highest score as the final result of polysemous words. Experiments show that PL-WSD model is greatly improved compared with other models.

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Machine Learning Approaches for Image-Based Screening of Cervical Cancer 3rd

Machine Learning Approaches for Image-Based Screening of Cer...

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3rd international conference on Data, Engineering, and Applications, IDEA 2021

作者： Rastogi, Priyanka Khanna, Kavita Singh, Vijendra CSE &IT Department The NorthCap University Gurugram India Delhi Skill Entrepreneurship University Delhi India Department of Computer Science UPES Dehradun India

ISBN: (纸本)9789811946868

Cervical cancer can be prevented if it is diagnosed at an early stage using screening methods. The need for automated cancer screening methods is emphasized due to the tedious task of cytotechnicians and medical experts, who spend hours analyzing the cellular abnormalities under the microscope. The objective of this review paper is to gain awareness from the recent researches on automated screening methods using image processing techniques, classical machine learning, and more recent deep learning approaches. The paper primarily focuses on the classification of cervical cell types, both binary and multiclass. It also provides a comprehensive understanding of the datasets and the performance metrics used in these studies. It targets cancer studies promote more focused researches to be undertaken in the future. The recent literature shows that deep-learning-based methods are quite popular in delivering promising results in image-based classification and segmentation tasks in diagnosing cervical cancer. The development of such automated systems can assist doctors or pathologists in a much quicker error-free decision-making process. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Decision support systems

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3rd international conference on Big Data and Security, ICBDS 2021

3rd International Conference on Big Data and Security, ICBDS...

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3rd international conference on Big Data and Security, ICBDS 2021

ISBN: (纸本)9789811908514

The proceedings contain 59 papers. The special focus in this conference is on Big Data and Security. The topics include: Research on Active Sampling with Self-supervised Model;research on Civil Aviation Economic Security Situation Assessment Model Based on Ant Colony Algorithm;a Supervised Learning Model for Detecting Ponzi Contracts in Ethereum Blockchain;community Detection Based on Deep Network Embedding with Dual Self-supervised Training;detecting Hybrid Anomalies Using an Unsupervised Approach in Online Social Networks;vehicle Road Privacy Recommendation System Equipped with Markov Chain;data-Driven Distribution Network Energy-Saving Planning Based on Cluster Division and High-Penetration Renewable Energy Access;state Machine Inference Method of Unknown Binary Protocol Based on Recurrent Neural Network;research and Judgment of Enterprise Energy Consumption Anomaly Based on Massive Data Clustering Algorithm;based on Data Mining New Energy Medium - and Long - Term Electricity Market Trading Power Decomposition Strategy;application of Machine Learning Algorithm in Art Field – Taking Oil Painting as an Example;using Multi-criteria Evaluation of E-learning System: A Methodology Based on Learning Outcomes;optimization on Service Function Chain Deployment for Cloud Network Collaborative Operation Platform;Research on Defect Intelligent Identification System Based on Cloud-Fog-Edge Cooperation for UAV Electric Power Inspection;anomaly Detection of Cloud Network Resource State Based on Deep Learning;Spinal Posture Recognition Device Using Cloud Storage and BP Neural Network Approach Based on Surface Electromyographic signal;research on Identification Method of Sensitive Data in Power System;research on Civil Aviation Economic Pricing Based on Equilibrium Game;design Guidance for Lightweight Object Detection Models.

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Application of Identity Resolution-based Digital Twin in the Entire Life Cycle of Aviation Products 22

Application of Identity Resolution-based Digital Twin in the...

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3rd Asia-Pacific conference on Image processing, Electronics and computers, IPEC 2022

作者： Wu, Dongdong Zhu, Yian Shi, Xianchen Zhou, Wei School of Computer Science Northwestern Polytechnical University Xi'an China School of Software Northwestern Polytechnical University Xi'an China

ISBN: (纸本)9781450395786

The continuous deepening of the construction of my country's IIoT identity resolution system needs to be applied to various fields to establish its Industrial IoT ecosystem. The research on Digital twin has also expanded from concept to practical application. Identity resolution and Digital twin each realize the "symbiosis and same growth"of products in the two dimensions of data and model. For the Product entire life cycle, the use of different rules for encoding information between companies will hinder the sharing of the Digital twin model, which will subsequently increase the difficulty of constructing the Digital twin scene. This article proposes a combination of identity resolution and digital twin, which has broken the barriers to data flow between enterprises. Finally, to realize the model sharing between different enterprises. In the field of aviation manufacturing, the two are organically combined. Use the IIoT platform to establish a full-element, multi-scale product twin model. Apply it to the full life cycle management of Aviation products and target several important life stages of Aviation products. To study the method and application of the corresponding twin scene model to realize the intelligent manufacturing of Aviation products. © 2022 ACM.

关键词： Life cycle

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Link Prediction Based on Pairwise Proximity Preserving Graph Neural Networks 1

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3rd international conference on Artificial Intelligence Logic and Applications, AILA 2023

作者： Huang, Xikun Li, Yangyang Fei, Chaoqun Wang, Chuanqing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China NCMIS Beijing China

ISBN: (数字)9789819978694

ISBN: (纸本)9789819978687

Link prediction is one of the key problems in network science and can be applied to many scenarios such as recommender system. Traditional link prediction methods are either based on heuristics or shallow network embedding methods which may either hardly generalize well or cannot optimize node representations and link probabilities simultaneously. Although the recently proposed graph neural network-based methods achieve promising performances, they do not preserve the original pairwise proximity at each hidden layer since non-linear operations may hinder it. In this paper, we propose a novel end-to-end link prediction method named Pairwise Proximity Preserving Graph neural network (PPPG), which can preserve the pairwise proximity at each layer. Specifically, inspired by graph signal denoising techniques, we preserve the structural pairwise proximity by solving an optimization problem after the non-linear operations at each layer. We evaluate our model on various standard link prediction benchmarks, and obtain competitive results. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Graph neural networks

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A Generalized Comprehensive Security Architecture Framework for IoT Applications Against Cyber-Attacks 3rd

A Generalized Comprehensive Security Architecture Framework ...

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3rd international conference on Recent Trends in Advanced Computing - Artificial Intelligence and Technologies, ICRTAC-AIT 2020

作者： Nakkeeran, M. Mathi, Senthilkumar Department of Computer Science and Engineering Amrita School of Engineering Coimbatore Amrita Vishwa Vidyapeetham Ettimadai India

ISBN: (纸本)9789811664472

Integration of apps through emerging Internet of Things (IoT) technology with edge computing opens up increased possibilities for building a smart network environment. The deployment of Industrial Internet of Things (IoTs/IIoT) sensors and devices for various purposes in smart cities is gaining momentum. Owing to edge computing, the central network and cloud technology end users are getting close enough. Increased deployment of these sensors and devices coupled with massive data processing gives attackers the right incentives. Most network assaults attempt to exploit potential IoT device inconsistencies and misconfigurations. Attackers are trying to spread the dynamism of malicious activities and to cripple the entire network environment. Edge computing threats and bugs are spread in a manner that they emanate from endpoints, IoT sensors, networking fabrics, and edge computing tools. It should take into account the scale emanating from the rapid proliferation of devices and the increasing potential for attacks. This paper provides a comprehensive end-to-end security solution framework with the detective model to identify anomalies in the networks by providing cross-layer security solutions. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Edge computing

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Throughput Enhancement in Wireless Sensor Network by Novel Genetic Algorithm-Fuzzy Method (NGA-F) 3rd

Throughput Enhancement in Wireless Sensor Network by Novel G...

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3rd international conference on VLSI, Communication and signal processing, VCAS 2020

作者： Prakash, N. Rajalakshmi, M. Nedunchezhian, R. Department of Electronics and Communication Engineering KIT-Kalaignarkarunanidhi Institute of Technology Coimbatore India Department of Computer Science and Engineering and Information Technology Coimbatore Institute of Technology Coimbatore India

ISBN: (纸本)9789811627606

Demodulating the unsafe hubs along with reducing the vitality squander in sensor hubs can drag out the life expectancy of remote sensor systems. By doing the examination, adaptive heuristic search algorithms and an adaptive neuro fuzzy inference system (ANFIS) framework were utilized to lessen the vitality misuse of sensors. Biased trust assessment was connected to look for unsafe hubs in the system for drawing out the life expectancy of the sensor network. Low-vitality versatile grouping chain that has some importance strategies were utilized for breaking down the outcomes. It was found that looking for destructive hubs having genetic algorithm (GA)—Adaptive Network-based Fuzzy Inference System (ANFIS) utilizing subjective trust assessment altogether expanded the life expectancy of WSNs. For assessment of the proposed technique that was utilized by the means of vitality of all sensors against the round, information that are obtained in base station, least vitality versus adjusts and number sensors that are alive sensors versus rounds. Likewise, the manuscript has the proposed strategy along with the results and Dual Fuzzy Logic-Cluster Protocol (DFLCP), Low-Energy Adaptive Clustering Hierarchy (LEACH), Centralized Low-Energy Adaptive Clustering Hierarchy (LEACH-C), Enhanced Distributed Energy Efficient Clustering (EDEEC), Hybrid Energy Efficient Distributed clustering (HEED). As results the proposed Novel Genetic algorithm with Fuzzy (NGA-F) strategy has high life time than different techniques. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fuzzy inference

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Performance of OpenFlow-based SDN on IoT network

Performance of OpenFlow-based SDN on IoT network

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The 3rd international conference on Distributed Sensing and Intelligent Systems (ICDSIS 2022)

作者： H. Jaadouni C. Saadi H. Chaoui Science and Engineering Laboratory of the National School of Applied Sciences of KénitraIbn Tofail Laboratory of Systems AnalysisInformation Processing and Industrial Management (LASTIMI) of EST Salé

Every day we are getting more and more connected devices to our connected network knotweed Internet of Things (IoT) so it requires new methods to secure the network and the data! So in our research to make the connected network we did enlarge the search to the Software-defined Network (SDN) is a way that permit the network is configurable and a centralized management the thing that lead to a dynamic management to the network

关键词： computer network management computer network performance evaluation Internet of Things software defined networking

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Automated Vehicle License Plate Recognition System: An Adaptive Approach Using Digital Image processing 1

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3rd international conference on Sustainable Advanced Computing, ICSAC 2021

作者： Rahman, Saidur Trisha, Tahmina Aktar Imran Hossain Imu, Md. Department of Electronics and Telecommunication Engineering Daffodil International University Dhaka Bangladesh Department of Computer Science and Engineering Daffodil Institute of IT Dhaka Bangladesh

ISBN: (数字)9789811690129

ISBN: (纸本)9789811690112

In the last twenty years, the number of vehicles has increased rapidly in our country. With this increase, it is gradually more difficult to track each vehicle for effective law enforcement and traffic management purposes. The growing rate of cars brings upon itself the need to rapidly check the lawfulness of the drivers. When traveling, there are several legal obligations a driver has to fulfill according to the law. In this paper, we proposed an automatic license plate recognition (ALPR) system is a digital image processing procedure that identifies the vehicle number plate without human involvement. It is a computer system that automatically detects and recognizes any digital image on the number plate. This system involves image preprocessing and edge detection using a canny edge detection algorithm, regional localization, and pytesseract used to identify the English characters in the number plate efficiently as well as with less computational complexity. This system simulates an accuracy rate of 97% (approximate) with a comparison of the average processing time of 0.75 s. Our automated system might be highly effective in real-time traffic control, security enhancement in parking lots in shopping malls, hospitals, airports, as well as in electronic toll collection. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Optical character recognition

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