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Smart Monitoring and Guidance System for Parking Spaces 5

Smart Monitoring and Guidance System for Parking Spaces

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

作者： Manvanth, G.S. Pavan Kumar, A. Priyanka, Valipe Devi Goduguluri, Varshitha Ravish, Roopa Pes University Department of Computer Science and Engineering Karnataka Bengaluru India

ISBN: (纸本)9798350383522

A parking system refers to the infrastructure and technology used to manage and facilitate the parking of vehicles in a specific area. These systems are designed to streamline the process of finding parking spaces, enhance efficiency, and improve overall traffic management. The proposed system is designed to address the challenges faced by open space parking spaces in major metropolitan cities. The prevailing issue of locating parking spaces in busy urban settings is tackled using Machine Learning (ML) model. Smart Monitoring and Guidance system is a ML based technology which allows the users to find vacant parking slots in a given area. The system uses ML model over internet of Things (IoT) based solutions as scaling and maintenance is easier using ML models. The system provides real time information to the users about the total number of parking slots available at a parking space using image processing. The users can select a parking space of their choice. Upon selecting a suitable parking space, users are provided with real-time navigation assistance to the parking space of their choice. ML model improves the overall efficiency, reliability, and robustness of the system. The system obtains parking information of multiple parking spaces by processing their video footages concurrently. The system provides users with real-time navigation to the parking space thus providing the users and hassle free experience. © 2024 IEEE.

关键词： Directions assistance image Processing Machine Learning Parking issues Parking Monitoring Parking slot availability Real-time navigation Real-Time Processing Smart city solutions Support Vector Classifier Time-saving Traffic reduction

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2nd international conference on Advances in Information and Communication technology, ICTA 2023

2nd International Conference on Advances in Information and ...

引用

2nd international conference on Advances in Information and Communication technology, ICTA 2023

ISBN: (纸本)9783031508172

The proceedings contain 35 papers. The special focus in this conference is on Advances in Information and Communication technology. The topics include: A Real-time Crowd Density Level Detection System;an Architecture for More Fine-Grained Hidden Representation in Named Entity Recognition for Biomedical Texts;application of Deep Learning Methods for Forest Fire Intelligent image Processing;choosing Data Points to Label for Semi-supervised Learning based on Neighborhood;classification of Fermentation Levels of Cacao Beans (Theobroma cacao L.) Using Sensing technology and Neural Networks;DCDynUnet: Deep Supervision Attention Context for Brain Segmentation;enhancing Wildfire Detection Using Semi-supervised Fuzzy Clustering on Satellite imagery;Evaluating the Performance of Some Deep Learning Model for the Problem of Emotion Recognition based on EEG signal;a Novel Arm Bone Fracture Detection Using Deep Learning;feature Reduction for Interpretability of Neuro-Fuzzy Classifier;improved Accuracy of Path System on Creating Intelligence Base;the Vehicle Routing Problem with Drones for Fresh Agricultural Products;ViT-SigNet: Combining Deep CNN and Vision Transformer for Enhanced Signature Verification;combining Local Search and Multi-objective Optimization Algorithm in signalized Intersection Optimization;Comparative Evaluation of PRR and PODA Methods for Model Order Reduction in Electrical Circuits;data-Driven Narratives: Unleashing the Potential of R for Journalistic Storytelling;dynamic Analysis of Capsubot Model in Liquid Environment by Numerical Method;genetic Programming–A Preliminary Study of Knowledge Transfer in Mutation;improvement of Spectral Clustering Method in Social Network Community Detection;a Systematic Review of Artificial Intelligence in Geographic Information systems;probable Characteristics of Multi-channel Queuing systems with "Impatient" and "Patient" Claims.

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A Study on Deep Learning-based image Target Identification Techniques 5th

A Study on Deep Learning-Based Image Target Identification T...

引用

5th international conference on 3D Imaging Technologies—Multidimensional signal Processing and Deep Learning, 3DIT-MSP and DL 2023

作者： Wang, Yining College of Electronic Information and Optical Engineering Taiyuan University of Technology Shanxi Taiyuan China

ISBN: (纸本)9789819751808

This study aims to explore deep learning-based image target recognition methods to improve the performance of target detection and classification in the field of computer vision. The experiments use satellite-acquired remote sensing images of moving objects, including four target categories such as buses, cars, bicycles and ships. In model training, we performed parameter optimisation by stochastic gradient descent algorithm and set the training period to 12. To validate the model’s effectiveness, we compare the improved R-CNN (Region-based Convolutional Neural Network), traditional CNN (Convolutional Neural Network) and Faster-RCNN (Faster Region-based Convolutional Neural Network) models, and generate confusion matrices to evaluate their performance. The experimental results show that the improved model exhibits excellent performance in recognition of different types of target objects, especially for larger targets. This research provides reliable experimental support for the application of deep learning in the field of image target recognition and is expected to promote further development and innovation in this field. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Convolutional neural networks

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Overview of Automatic Modulation Recognition Methods 2

Overview of Automatic Modulation Recognition Methods

引用

2nd IEEE international conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Xie, Shaoxiong Ye, Jun Hainan University Key Laboratory of Internet Information Retrieval of Hainan Province School of Cyberspace Security Haikou China

ISBN: (纸本)9798350347456

Blind detection and identification processing such as communication signal detection, modulation identification, and individual radiation source identification under non-cooperative reception conditions is an important basis for radio spectrum monitoring and battlefield communication reconnaissance and confrontation. However, due to adverse factors such as strong interference and fast-changing electromagnetic environment during non-cooperative reception, complex and diverse communication signal systems, and inability to fully grasp signal prior information, blind detection and identification of communication signals are extremely challenging. This article comprehensively sorts out the modulation recognition algorithm. The DL-based AMR algorithm is systematically reviewed from the three levels of the data set, network model, and final performance. Finally, the existing problems, potential research directions, and conclusions of AMR are outlined. © 2023 IEEE.

关键词： Decision theory

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Combined Wavelet and multiwavelet-based Convolutional Neural Network (CWM-CNN) for Remote Sensing image Super Resolution

Combined Wavelet and multiwavelet-based Convolutional Neural...

引用

international conference on Computer Vision and internet of Things 2023, ICCVIoT 2023

作者： Sandana, Sudaroli J. Thool, Kunal Vijay Deivalakshmi, S. Department of Electronics and Communication Engineering National Institute of Technology Tiruchirappalli India

ISBN: (纸本)9781839539848

Acquiring remote sensing (RS) images with high pixel resolution quickly and easily in geographic information systems is extremely important. Existing Convolutional Neural Network (CNN) models generally construct a network with a massive number of layers and parameters, resulting in high computational complexity and considerable memory consumption. To overcome this issue, a Combined Wavelet and Multiwavelet Transform based Convolutional Neural Network (CWM-CNN) by fusing the properties of discrete wavelet transform (DWT) and multiwavelet transform (MWT) with smaller number of convolutional layers is proposed. The primary concept of the proposed technique is to combine Wavelet and Multiwavelet Transformed images for enhancing the resolution of the RS images. Wavelet and multiwavelet transforms are employed in the proposed work to extract shallow features from the input image, and a feature extraction block (FEB) with a compact 3-layer CNN is designed to extract deep features to improve image resolution. Three different RS image datasets, including the NW-VHU dataset, the AID Dataset, and the UCMerced Benchmark Dataset, are utilized to analyze the outcome of the proposed method. The results reveal that the proposed method outperforms other current models in terms of performance while using significantly less parameters. © The Institution of Engineering & technology 2023.

关键词： Discrete wavelet transforms

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Intelligent Traffic Light System based on IoT 2

Intelligent Traffic Light System based on IoT

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2nd international conference on Automation, Computing and Renewable systems, ICACRS 2023

作者： Gupta, Rohan Singh, Ankit Kumar Tewari, Pratistha Pankaj Dabral, Suhani Dept. of ECE UIE Chandigarh University Mohali India Dept. of CSE UIE Chandigarh University Mohali India

ISBN: (纸本)9798350340235

With rise in urbanization there has been an increase in traffic density, resulting in various traffic related issues like traffic congestion and increased air pollution. Hence traffic issues are one of the biggest issues faced by the people indaily life and needs to be handled by the government andadministration in an effective, practical and smart way. In smarttimes when internet has solution for most of the human problems, thenwhy not use IoT to solve road traffic problems. The Intelligent Traffic Light system based on IoT and traffic density is a modern approach towards existing traffic system which works on real time data analysis using ultrasonic sensor and gas *** technology is intended to handle traffic congestion by automatically modifying traffic signal timings at each interaction based on traffic density. Its goal is to increase road safety, minimize traffic jams, and improve overall traffic flow. A smart method for the emerging smart world. The unique partof the proposed system is the addition of gas sensor which will measure the level of air pollutants and accordingly with ultrasonic sensor which measures density of traffic to reduce traffic congestion and improve air quality. © 2023 IEEE.

关键词： gas sensor internet of Things real time data analysis traffic density ultrasonic sensor

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Security of images Using Pascal's Triangle Chaotic Encryption Scheme and with Biometric Authentication in Cloud Storage 4

Security of Images Using Pascal's Triangle Chaotic Encryptio...

引用

4th international conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2024

作者： Gupta, Raghav Gullapalli, Manasa Suseela, G. School of Computing Science and Engineering Srm Institute of Science and Technology Department of Networking and Communications Tamil Nadu Kattankulathur603203 India School of Computing Science and Engineering Faculty of Engineering and Technology Srm Institute of Science and Technology Department of Networking and Communications Tamil Nadu Kattankulathur603203 India

ISBN: (纸本)9798350343670

A key component of cloud computing is cloud storage, which allows data to be stored on remote servers. The result is a reduction in the amount of storage space required on local devices, allowing data to be accessed from anywhere with an internet connection. Furthermore, cloud storage is more secure than local storage due to the use of encryption and other security measures by professional providers. This is a practical and cost-effective solution to store large images required to be safeguarded from malicious black hat hackers. images are the most valuable yet vulnerable form of data that can be used to track down user activities and taken advantage by hackers, used to commit identity theft, fraud. Issues concerning the security and privacy of images saved in the cloud have arisen as cloud storage has grown in popularity. The proposed method will focus on the encryption of images using a chaotic encryption scheme based on Pascal's triangle. The user will authenticate their identity before uploading images to cloud storage and likewise confirm their authentication in the process of retrieval of an image. Such a secure system is better than traditional security methods for password settings as it cannot be easily stolen. Additionally, this method is more secure than other methods due to its complex encryption mechanisms, making it impossible to guess or steal the encryption key. In addition to providing extra security for sensitive images, biometric authentication will offer a stronger method of verifying and validating users on the cloud. © 2024 IEEE.

关键词： AWS Rekognition Chaotic systems Cloud Security Confusion Diffusion Facial Authentication image Encryption image Shuffling Pascal's Triangle Transform

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An image encryption algorithm based on multiple chaotic systems and DNA encoding 14

An image encryption algorithm based on multiple chaotic syst...

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14th international conference on Measuring technology and Mechatronics Automation, ICMTMA 2022

作者： Jiang, Feng-Bai Zhang, Xue-Feng Jiang, Wen School of Cyberspace Security Xi'an University of Posts and Telecommunications Xi'an710121 China National Internet Emergency Center Beijing100029 China

ISBN: (纸本)9781665499781

Aiming at the problems of image encryption algorithm in terms of security and encryption effect, an image encryption algorithm based on multiple chaotic maps and DNA encoding is proposed. First, using Logistic map to randomly scramble the rows and columns of the plaintext image, and convert the result into a binary matrix;second, according to the DNA coding rules, convert the binary matrix into a DNA matrix, and use 2 D - L S M M map and Logistic-Sine system to perform in DNA encoding operation, X O R operation is performed on the obtained encoding matrix to obtain an encrypted DNA matrix;finally, according to the DNA decoding rules, the encrypted DNA matrix is converted into a digital image to obtain a ciphertext image. Experimental simulation and performance analysis show that the algorithm has better encryption and decryption effects, larger key space, and higher security and robustness. © 2022 IEEE

关键词： Chaotic systems

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Implementation of AKKF-based Multi-Sensor Fusion Methods in Stone Soup 27

Implementation of AKKF-based Multi-Sensor Fusion Methods in ...

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27th international conference on Information Fusion (FUSION)

作者： Wright, James S. Sun, Mengwei Davies, Mike E. Proudler, Ian K. Hopgood, James R. Dstl Dstl Porton Bldg 5Rm 101 Salisbury SP4 0JQ Wilts England Cranfield Univ Sch Aerosp Transport & Mfg SATM Coll Rd Cranfield MK43 OAL Beds England Univ Edinburgh Inst Imaging Data & Commun Edinburgh EH9 3FG Midlothian Scotland Univ Strathclyde Ctr Signal & Image Proc CeSIP Dept Elect & Elect Engn Glasgow G1 1XW Lanark Scotland

ISBN: (纸本)9798350371420;9781737749769

This paper explores the increasing demand for accurate and resilient multi-sensor fusion techniques, particularly within 3D tracking systems enhanced by drone technology. Employing the adaptive kernel Kalman filter (AKKF) methodology within the Stone Soup framework, our research seeks to develop robust fusion approaches capable of seamlessly amalgamating data from a multi-sensor arrangement with fixed ground sensors and dynamic sensors mounted on drones. By capitalising on the adaptive nature of the AKKF, we aim to refine the precision and dependability of 3D object tracking in intricate scenarios. Through empirical evaluations, we illustrate the effectiveness of our proposed AKKF-based fusion strategies in enhancing tracking performance within the Stone Soup framework, thus contributing to the advancement of multi-sensor fusion methodologies within this framework.

关键词： Adaptive kernel Kalman filter sensor fusion Stone Soup 3D Tracking

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Hybrid Color image Compression Using signals Decomposition with Lossy and Lossless Coding Schemes 5

Hybrid Color Image Compression Using Signals Decomposition w...

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5th international conference on Information technology, Applied Mathematics and Statistics, ICITAMS 2023

作者： Aljumaily, Hala Abdulsalam George, Loay E. Baghdad University Baghdad Iraq University Of Information Technology And Communication Baghdad Iraq

ISBN: (纸本)9798350335118

This paper proposes a new, improved compression technique to compress color images. Compression knows days have become more critical because of the increasing demand for internet use and the exchange of many images, videos, and audio. This technique converts an image to YUV. The signal decomposition divides the image into significant components (C1) and small components (C2) parts;big indicates the energetic Component, and the detail is the small Component. Each Component is passed through different processing steps. The most vibrant part is passed through sequences of lossless coding steps to preserve the quality of the main features. The included coding steps are Bit plane Coding followed by Quadtree Coding. Meanwhile, the detailed Component was passed through a series of lossy coding steps using a controlled wavelet-based error criterion and quantization. Also, delta pulse code modulation (Delta PCM) was used to encode the (LL) component of the image due to its significance and to avoid causing significant distortions. While the rest components (LH, HL, HH) by discarding the small Bit plane and only encode the most important planes, the output of each encoded Bit plane is handled using Quadtree Coding. As a last stage of the energetic and detailed components, an adaptive shift coding. The proposed technique was tested on Lena and Baboon images;testing results indicated that the suggested system could produce a good compression ratio while preserving the image's quality under control © 2023 IEEE.

关键词： image compression

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