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Comparative Study of Implementation of Very Deep Super Resolution Neural Network and Bicubic Interpolation for Single Image Super Resolution Quality Enhancement

Comparative Study of Implementation of Very Deep Super Resol...

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International Conference on Applied Electromagnetics, Signal Processing and communication (AESPC)

作者： Ganesan P M. Ravichandran B.S. Sathish L.M.I.Leo Joseph G. Sajiv R. Murugesan Dept. of Electronics and Communication Engineering Vidya Jyothi Institute of Technology Hyderabad India Dept. of Computer Science Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Dept. of Computer Science Engineering AI Sri Venkateshwara College of Engineering Bengaluru India Dept. of Electronics and Communication Engineering SR University Warangal Telangana India Saveetha School of Engineering SIMATS Chennai India Dept. of Electronics and Communication Engineering Narshima Reddy Engineering College Secunderabad India

To improve the resolution and quality of a low level image, single image super resolution (SISR) is a challenging endeavor in the turf of computer vision. It is essential to many applications, including image editing, security systems, medical imaging, and others. In order to increase the spatial quality of a low level image, SISR attempts to approximate the high frequency details that are missing from the image. The field was formerly based on manually created features and interpolation techniques, but current developments in deep learning have completely changed it. The suggested work compares the effectiveness of bicubic interpolation and neural network based very deep super resolution for single image super resolution image quality improvement. Utilizing blind and complete reference picture quality measures, the effectiveness of the two approaches is evaluated. The effectiveness of the very deep super resolution for single image is clearly demonstrated by the experimental results.

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Electric Vehicle Charging system Using RFID and IoT for Enhanced User Experience

Electric Vehicle Charging System Using RFID and IoT for Enha...

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IEEE Middle East and North Africa communications Conference (MENACOMM)

作者： Md Mehedi Hassain Injamul Haque Jamil Md Mahmudul Hoque Md. Jahid Hasan Dept. of Electrical & Electronics Engineering International Islamic University Chittagong Chittagong Bangladesh Dept. of Computing & Mathematical Sciences University of Greenwich London United Kingdom Dept. of Computer Science & Engineering CCN University of Science and Technology Cumilla Bangladesh Dept. of Information & Communication Technology Comilla University Cumilla Bangladesh

ISBN: (数字)9798331519957

ISBN: (纸本)9798331519964

Electric vehicles (EVs) are surging in popularity globally, offering a greener and more energy-efficient alternative to traditional cars. Our research aims to develop an RFID based system designed to automate EV charging with minimal user input. This system integrates RFID readers, tags, a microcontroller, and a relay module to manage and monitor charging sessions efficiently. An IoT platform supports real time monitoring and remote control, while a secure payment mechanism handles transactions seamlessly. RFID tags identify vehicles for automatic charging initiation, and the relay module prevents overcharging by disconnecting power after a set time. The system uses MQTT for data transmission and offers real-time insights into energy use and account balances. All information is updated and displayed in real-time on the server. MySQL ensures scalability, enabling effective handling of large volumes of data. The mobile application dashboard provides a view of the charging and discharging processes for user monitoring, and an email notification is sent after the recharge. EV battery charging status is monitored through visual graphs. Key benefits include a streamlined user experience, improved charging management, and support for EV adoption. This innovation advances sustainable mobility with a user friendly, efficient charging solution.

关键词： Visualization Technological innovation Transportation Real-time systems Electric vehicle charging User experience Energy efficiency Relays Monitoring Radiofrequency identification

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Virtual Reality Based Medical Training Simulator and Robotic Operation system

Virtual Reality Based Medical Training Simulator and Robotic...

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Recent Progresses in Science, engineering and Technology (ICRPSET), International Conference on

作者： Md. Mustafizur Rahman Md Fatin Ishmam Md. Tanvir Hossain Md. Emdadul Haque Dept. of Information and Communication Engineering Dept. of Computer Science and Engineering University of Rajshahi Rajshahi Bangladesh

In the medical sector learning about the human body and practicing surgeries, the medical students need a real human body which is very costly. Repeatedly practice or undone after practice is almost impossible with the human body. Human anatomy, physiology, etc. subjects are very hard to understand and learn from books and images. Learning surgery on living humans is sometimes unethical and trainee surgeons has to struggle to learn rare surgeries. To solve these problems we use virtual reality (VR) to build a medical training simulator that can provide medical students better understanding and learning about the human body through 3D models of the body. Students can get an interactive learning experience and see how organs work from the molecular level and perform several operations. Since this is a simulation everything a new learner will do can be undone and re-practiced. On the other hand skilled surgeons are not available in all places in the country especially in remote places. A patient who needs the critical surgical treatment has to travel to a city to take the treatment by the expert surgeons. To solve this problem in this project we also connect a robot to our VR based system. A skilled surgeon can operate in the virtual environment from a distant place using the robot. The vision system of the robot can be realized by the surgeon through VR headset and he or she feels like, he or she is present there. Surgeons can control the robotic hands and tools necessary to perform the surgery from the remote place. This will reduce the trouble of patients traveling from remote places to city area for surgery. We implement the demo system in the lab and show some results which indicate the applicability of the proposed system.

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A Robust Blind Watermarking Technique for Improved Medical Image Security

A Robust Blind Watermarking Technique for Improved Medical I...

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2023 International Conference on system, Computation, Automation and Networking, ICSCAN 2023

作者： Shankar, A. Yazhinian, S. Kamaleshwar, T. Department of Electronics and Communication Engineering Manakula Vinayagar Institute of Technology Puducherry India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Dept. of Computer Science & Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350315127

Watermarking serves as a protective approach for medical data which ensures protection against illegal access. This new method uses wavelet decomposition to analyze and visualize images with varying resolutions, mirroring the human visual system. Watermarks are strategically added to the high-frequency subbands of wavelet-transformed images remaining imperceptible to the human eye, thereby enhancing the security of the watermarking scheme. However, the limitations of existing wavelets in detecting singularities across different frequency bands necessitated the development of novel filter designs capable of unveiling singularities in all orientations. Here it introduces innovative nontensor product wavelet filter banks, employing special symmetric matrices to uncover singularities comprehensively. Experimental investigations demonstrate the superiority of these new wavelet filter banks in singularity detection compared to conventional wavelets. Building upon these advancements, a modified significant difference watermarking algorithm is proposed, further enhancing the security of medical image data © 2023 IEEE.

关键词： Wavelet decomposition

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Photonic Spiking Convolutional Neural Networks for High-Speed Image Processing

Photonic Spiking Convolutional Neural Networks for High-Spee...

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2021 IEEE Photonics Society Summer Topicals Meeting Series, SUM 2021

作者： Skontranis, Menelaos Sarantoglou, George Bogris, Adonis Mesaritakis, Charis Dept. Information and Communication Systems Engineering School of Engineering University of the Aegean Samos Greece Dept. Informatics and Computer Engineering University of West Attica Aigaleo Greece

ISBN: (纸本)9781665416009

A multi-layer photonic spiking convolutional neural network is presented, based on miniaturized VCSELs, targeting image classification. Spatial information is encoded using a time multiplexing scheme providing a radical reduction of physical neuron-count. Hardware-friendliness is enhanced by exploiting unsupervised spike-timing dependent plasticity. © 2021 IEEE.

关键词： Convolutional neural networks

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Web Application-Based Enhanced Esophageal Disease Diagnosis in Low-Resource Settings

Web Application-Based Enhanced Esophageal Disease Diagnosis ...

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IEEE International Conference on Biomedical engineering, computer and Information Technology for Health

作者： Abdullah Al Masum Zishad Hossain Limon Md Ariful Islam Md Shahidur Rahman Mahbub Khan Sheikh Shemanto Afridi Md. Redwan Ahmed Shafiur Rahman Dept. of Information Technology Westcliff University CA USA Dept. of Computer Science Westcliff University CA USA Dept. of Business Administration International American University CA USA Dept. of Engineering management Westcliff University CA USA Dept. of Management Information System Pacific State University CA USA Dept. of Computer Science and Engineering East West University Dhaka Bangladesh Dept. of Software Engineering Daffodil International University Dhaka Bangladesh

ISBN: (数字)9798331534356

ISBN: (纸本)9798331534363

An essential part of the digestive system, the esophagus permits food and liquids to move easily from the throat to the stomach. Traditional diagnostic techniques, such as endoscopy and biopsy, are invasive and resource-intensive, making them less practical in resource-constrained environments. To address these challenges, we proposed utilizing a hybrid Deep Learning (DL) model called GAN-EfficientNet, which combines the power of Generative Adversarial Networks (GAN) and EfficientNet to effectively classify esophageal diseases. Our approach employs advanced image preprocessing techniques and data augmentation methods to enhance the diversity and balance of the dataset. Feature extraction using the Spatial Gray Level Dependence Method (SGLDM) and Principal Component Analysis (PCA) significantly reduces computational complexity without compromising accuracy. We explored both binary and multiclass classification methods, recognizing their crucial roles in various diagnostic scenarios. Binary classification distinguishes between normal and diseased states, essential for initial screening, while multiclass classification identifies specific esophageal diseases, aiding in personalized treatment plans. The GAN-EfficientNet model demonstrated exceptional performance, achieving an impressive F1 score of 99.44% for binary classification and 99.64% for multiclass classification. Additionally, we developed a web application that facilitates quick and precise disease diagnosis, particularly advantageous in areas with limited resources. This tool significantly improves patient outcomes through early detection, leading to reduced healthcare costs and less burden from advanced esophageal diseases.

关键词： Deep learning Accuracy Computational modeling Generative adversarial networks Feature extraction Data augmentation Data models Medical diagnosis Diseases Principal component analysis

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Automatic Digit and Alphabet Recognition Based Online Toll Collection system

Automatic Digit and Alphabet Recognition Based Online Toll C...

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2021 International Conference on Information and communication Technology for Sustainable Development, ICICT4SD 2021

作者： Hossen, Md. Sahadat Akter, Mahmuda Saifuddin, Khaled Mohammed Premier University Dept. of Computer Science and Engineering Chittagong4000 Bangladesh Khulna University of Engineering and Technology Dept. of Electronics and Communication Engineering Khulna9203 Bangladesh

ISBN: (纸本)9781665414609

Radio frequency identification (RFID) based automatic highway toll collection system has become very popular among developed countries. However, RFID is not feasible for developing countries to embed with each vehicle since it is very costly. Moreover, as metal objects can influence Radio Frequency (RF) field, intently the nearness of any metal object while reading RFID information may result in unwanted noise. These problems are still significant concerns. We propose a vehicle number plate recognition-based automated toll collection system to address these issues, which is more efficient, reliable, and cost-effective for widely use. In this research, the Normalized Cross-Correlation (NCC) based template matching algorithm is exploited for character recognition from each vehicle's number plate. After recognizing characters from a number plate successfully, a fixed amount of toll fee is charged automatically according to the vehicle's category. © 2021 IEEE.

关键词： Template matching

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Enhancing Performance in Hybrid Satellite-Terrestrial Networks: A Novel Joint NOMA-NC Approach

Enhancing Performance in Hybrid Satellite-Terrestrial Networ...

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IEEE Conference on Global communications (GLOBECOM)

作者： Michail Karavolos Nektarios Moraitis Lefteris Tsipi Demosthenes Vouyioukas Dept. of Information and Communication Systems Engineering University of the Aegean Samos Greece School of Electrical and Computer Engineering National Technical University of Athens Zografou Greece Dept. of Digital Systems University of Piraeus Piraeus Greece

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

An appealing alternative towards dealing with mobility and coverage challenges in future wireless networks, are hybrid satellite-terrestrial networks (HSTNs). The combination of network coding (NC) and non-orthogonal multiple access (NOMA) techniques, have recently gained popularity due to their performance gains in improving the quality of a wireless transmission and exploiting the accessible spectrum. This paper introduces a joint NOMA-NC approach, integrated to an HSTN comprising a satellite, a terrestrial base station (BS), and multiple ground-based mobile terminals (MTs). The suggested method facilitates a cluster of end-users to be concurrently served through NOMA from a satellite using optimal power allocation, whereas the BS utilizes random linear NC to augment the MTs’ reception in the event of errors. The simulation results confirm the effectiveness of the proposed methodology in improving system sum throughput, demonstrating substantial enhancements compared with both OMA with NC, and standalone NOMA and OMA approaches. The resilience of the suggested method is proved, improving the sum throughput even at low power transmissions and in the worst case channel conditions.

关键词： NOMA Satellites Wireless networks Simulation Network coding Space-air-ground integrated networks Throughput Hybrid power systems Resource management Resilience

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Exploring the Quality of Service Impacts of Cloud Computing over Wireless Networks

Exploring the Quality of Service Impacts of Cloud Computing ...

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2024 International Conference on E-Mobility, Power Control and Smart systems, ICEMPS 2024

作者： Gopal, Santhosh Kumar Mohammed, Abdul Sajid Saddi, Venkata Ramana Jiwani, Nasmin Logeshwaran, J. Sciences CharlotteNC United States School of Computer and Information Sciences University of The Cumberlands KY United States Ace American Insurance Chubb Group RaleighNC United States University of The Cumberlands Dept. of Information Technology WilliamsburgKY United States Sri Eshwar College of Engineering Department of Electronics and Communication Engineering Coimbatore India

ISBN: (纸本)9798350394399

Cloud computing is a paradigm that enables users to access statistics and programs through the use of a virtualized infrastructure. As such, it could be leveraged to lessen the prices of strolling an allotted system, even at the same time growing its competencies and flexibility. Unfortunately, cloud computing additionally has a big effect on the great of service of the underlying Wi-Fi community. In this paper, we discover the best carrier influences of cloud computing over wi-wireless networks in phrases of latency, throughput, and packet loss. Wi-Fi, we talk about the demanding situations and solutions associated with integrating Wi-Fi networks with cloud computing architectures. We then evaluate the overall performance of different eventualities, consisting of using 4G and 5G, as well as baseline overall performance without cloud integration. Our outcomes show that cloud computing can improve the general quality of service of Wi-Fi wireless networks despite the fact that there may be full-size variations between exceptional community generations. © 2024 IEEE.

关键词： Cloud computing

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Crossover Methods Comparison in Flood Evacuation Route Optimization

Crossover Methods Comparison in Flood Evacuation Route Optim...

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International Conference on Artificial Intelligence in Information and communication (ICAIIC)

作者： M. Adnan Nur Hazriani Nur Khaerat Nur Dept. of Informatics Handayani University Makassar Indonesia Dept. of Computer System Handayani University Makassar Indonesia Dept. of Civil Engineering Fajar University Makassar Indonesia

This study aims to implement the genetic algorithm by testing the appropriate crossover methods in order to obtain optimal disaster evacuation routes based three main indicators, namely travel time, possible transportation mode, and affected road conditions. The research phase begins with establishing a flood-affected area scenario consisting of the victim's initial location, evacuation location, routing areas, affected road conditions, distance, as well as travel time. The genetic algorithm is applied by representing the genes and chromosomes based on the available data, generating the initial population and calculating the fitness value. At the stage of determining the parent in forming a new individual, roulette wheel selection is used. For the crossover method to produce new individuals, there are 3 methods tested namely single-point, two-point and uniform crossover. The new formed individuals are then mutated with a probability level of 0.1. The last stage is to form a new population by sorting individuals with the highest fitness value. These processes took place with an iteration limit of 1000. Based on the results of the implementation and tests conducted, the uniform crossover method has the most optimal results with accuracy 90% and highest fitness value of 0.896. Meanwhile, the two others methods two-point and single-point have extremely lower accuracy which are 70% and 60% respectively. This result confirmed the statement of previous research which convinced that the uniform crossover is the most effective crossover method.

关键词： Roads Sociology Wheels Transportation Routing Floods Statistics

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