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25th International Conference on Digital Image computing: Techniques and Applications, DICTA 2024

作者： Mirza, Inzela Iqbal, Shahzaib Alhaqbani, Bandar Alshammari, Bandar Khan, Tariq Razzak, Imran Department of Computing Islamabad Pakistan Tcc Research and Development Labs Technology Control Company Riyadh Saudi Arabia Computer and Information Sciences College Jouf University Saudi Arabia School of Computer Science and Engineering University of New South Wales Sydney Australia

ISBN: (纸本)9798350379037

Over recent years, deep convolutional neural networks have advanced the field of face recognition in both verification and identification applications. In this paper, we present ShadowNets, a highly efficient and compact face recognition network. We employed multiple shadow blocks in a cascading manner where the output of each shadow block is given as the input to the next shadow block. By integrating the advantages of Focal Modulation Blocks, Shadow Block and Ghost Modules, our proposed ShadowNets achieves superior face recognition performance, optimized specifically for edge devices. This network architecture not only minimizes computational costs and storage needs but also delivers high accuracy, making it suitable for deployment in edge environments. Our extensive experiments on challenging benchmark face datasets showcase the outstanding performance by achieving accuracy 98.85% on LFW, 84.37% on CFP-FP, and 91.23% on AgeDB-30 which validates the effectiveness of ShadowNets over state-of-the-art lightweight and deep face recognition models. © 2024 IEEE.

关键词： Convolutional neural networks

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Empowering Diagnosis: Cutting-Edge Segmentation and Classification in Lung Cancer Analysis

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computers, Materials & Continua 2024年第6期79卷 4963-4977页

作者： Iftikhar Naseer Tehreem Masood Sheeraz Akram Zulfiqar Ali Awais Ahmad Shafiq Ur Rehman Arfan Jaffar Faculty of Computer Sciences&Information Technology The Superior UniversityLahore54000Pakistan Intelligent Data Visual Computing Research(IDVCR) Lahore54000Pakistan Information System Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia School of Computer Science and Electronic Engineering(CSEE) University of EssexWivenhoe ParkColchesterCO43SQUK

Lung cancer is a leading cause of global mortality *** detection of pulmonary tumors can significantly enhance the survival rate of ***,various computer-Aided Diagnostic(CAD)methods have been developed to enhance the detection of pulmonary nodules with high ***,the existing method-ologies cannot obtain a high level of specificity and *** present study introduces a novel model for Lung Cancer Segmentation and Classification(LCSC),which incorporates two improved architectures,namely the improved U-Net architecture and the improved AlexNet *** LCSC model comprises two distinct *** first stage involves the utilization of an improved U-Net architecture to segment candidate nodules extracted from the lung ***,an improved AlexNet architecture is employed to classify lung *** the first stage,the proposed model demonstrates a dice accuracy of 0.855,a precision of 0.933,and a recall of 0.789 for the segmentation of candidate *** suggested improved AlexNet architecture attains 97.06%accuracy,a true positive rate of 96.36%,a true negative rate of 97.77%,a positive predictive value of 97.74%,and a negative predictive value of 96.41%for classifying pulmonary cancer as either benign or *** proposed LCSC model is tested and evaluated employing the publically available dataset furnished by the Lung Image Database Consortium and Image Database Resource Initiative(LIDC-IDRI).This proposed technique exhibits remarkable performance compared to the existing methods by using various evaluation parameters.

关键词： Lung cancer segmentation AlexNet U-Net classification

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Wind Driven Optimization-Based Medical Image Encryption for Blockchain-Enabled Internet of Things Environment

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computers, Materials & Continua 2022年第11期73卷 3219-3233页

作者： C.S.S.Anupama Raed Alsini N.Supriya E.Laxmi Lydia Seifedine Kadry Sang-Soo Yeo Yongsung Kim Department of Electronics&Instrumentation Engineering V.R.Siddhartha Engineering CollegeVijayawada520007India Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Computer Science and Engineering Malla Reddy Engineering College(A)Hyderabad500100India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Applied Data Science Noroff University College4612KristiansandNorway Department of Computer Engineering Mokwon UniversityDaejeon35349Korea Department of Technology Education Chungnam National University 99Daehak-roYuseong-guDaejeon34134Korea

Internet of Things(IoT)and blockchain receive significant interest owing to their applicability in different application areas such as healthcare,finance,transportation,*** image security and privacy become a critical part of the healthcare sector where digital images and related patient details are communicated over the public *** paper presents a new wind driven optimization algorithm based medical image encryption(WDOA-MIE)technique for blockchain enabled IoT *** WDOA-MIE model involves three major processes namely data collection,image encryption,optimal key generation,and data ***,the medical images were captured from the patient using IoT ***,the captured images are encrypted using signcryption *** addition,for improving the performance of the signcryption technique,the optimal key generation procedure was applied by WDOA *** goal of the WDOA-MIE algorithm is to derive a fitness function dependent upon peak signal to noise ratio(PSNR).Upon successful encryption of images,the IoT devices transmit to the closest server for storing it in the blockchain *** performance of the presented method was analyzed utilizing the benchmark medical image *** security and the performance analysis determine that the presented technique offers better security with maximum PSNR of 60.7036 dB.

关键词： Internet of things image security medical images encryption optimal key generation blockchain

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Speech Measuring Following Semiconductor Feature for Acoustic using Biodegradable Material 3

Speech Measuring Following Semiconductor Feature for Acousti...

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3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Upadhyay, Shrikant Kumar, Rakesh Kumar, Binod Kumari, Barkha Lakra, Ankita Mandal, Sampurna Department of Electronics and Communication Engineeing MLR Insitute of Technology Hyderabad India Wipro Engineering Edge Hyderabad India Facultyt of CSE & IT Jharkhand Rai University Ranchi India GH Raisoni College of Engineering and Management Pune India Faculty of Computing and IT Usha Martin Univerity Ranchi India Department of Computer Science and Engineering-Artifical Intelligence Brainware University Kolkata India

ISBN: (纸本)9798331527549

This research paper primarily focuses to identify the various feature removal presence used for addresser recognition and validation. The current template i.e. classical and typical are considered to examine its role in different acoustic surroundings and also try to measure feature removal in acoustic condition considering factors like jitters, noise, echo etc. which truly a factor that affect the speech performance and degrades the overall performance of any system. Effort has been put to inspect the attainment of various feature removal approach with the help of classifier considering different structures. The behavior of different feature extraction removal simulated using Hindi samples and it will be analysed in terms of efficiency and error rate. The result may be useful for suitable for existing as well as any proposed model by changing its classifiers. Speech of different ages as well groups are used to analysed and implementation using 16-bit TMS 320 C5X semiconductor devices with the feature extraction and algorithm may improve the overall efficiency of the proposed system. Bio-degradable material can also help to reduce the acoustic level at different of speaker identifications. The feature of semiconductor helps to understand and also add the improvements in proper selection of feature extraction that consume less time in evaluating the algorithm and provide better efficiency in different acoustic conditions. Biodegradable material has not used so far in various studies and biodegradable paly a very important role in acoustic condition as we are dealing with acoustic condition and it is very important to take care of acoustic to come up with better efficiency. © 2025 IEEE.

关键词： Semiconductor devices

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Automated 3D Urban Landscapes Visualization Using Open Data Sources on the Example of the City of Zagreb

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KN - Journal of Cartography and Geographic Information 2022年第2期72卷 139-152页

作者： Komadina, Adrian Mihajlović, Željka Department of Electronics Microelectronics Computer and Intelligent Systems Faculty of Electrical Engineering and Computing University of Zagreb Unska 3 Zagreb 10000 Croatia

Geographical location visualization is important to create virtual environments when performing simulations. This study uses publicly available data sources to create three-dimensional (3D) views of geographical locations, focusing on the city of Zagreb as a case study, and presents an automated solution that integrates data from four different sources to achieve this. Publicly available data sources (OpenStreetMap, Google Maps Elevation API, MapBox Static Images API) were used, and GIS Zrinjevac which is unique to Zagreb. Based on these sources, individual 3D objects were generated and displayed virtually in the form of an interactive 3D map. The proposed solution attempts to balance the differing levels of detail achieved using other techniques. The solution was implemented in the form of an application created using the Unity game engine. The results were analyzed to evaluate the solution’s validity and the created application’s performance. The analysis showed that the total execution time dependence is quadratically polynomial to the amount of retrieved data, and linear to the number of height map points. Examining the application’s update rate showed that the buildings and individual models used for polygon and point data had the greatest impact. Finally, possible improvements, alternative approaches, and advantages and disadvantages of the proposed solution are compared with other techniques used in this research area. © 2022, Deutsche Gesellschaft für Kartographie e.V.

关键词： Cartographic data Data visualization GIS Zrinjevac Google maps elevation API OpenStreetMap Virtual environment

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An Optimized Fuzzy Based Ant Colony Algorithm for 5G-MANET

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computers, Materials & Continua 2022年第1期70卷 1069-1087页

作者： R.Nithya K.Amudha A.Syed Musthafa Dilip Kumar Sharma Edwin Hernan Ramirez-Asis Priya Velayutham V.Subramaniyaswamy Sudhakar Sengan Department of Computer Science and Engineering Vivekananda College of Engineering for WomenTiruchengode637205Tamil NaduIndia Department of Electronics and Communication Engineering Kongunadu College of Engineering and TechnologyThottiam621215Tamil NaduIndia Department of Information Technology M.Kumarasamy College of EngineeringKarur639113Tamil NaduIndia Department of Mathematics Jaypee University of Engineering and TechnologyGuna473226M.P.India Business and Tourism Faculty Universidad Nacional Santiago Antunez De MayoloHuarazPeru Department of Computer Science and Engineering Paavai Engineering CollegeNamakkal637018Tamil NaduIndia School of Computing SASTRA Deemed UniversityThanjavur613401Tamil NaduIndia Department of Computer Science and Engineering PSN College of Engineering and TechnologyTirunelveli627152Tamil NaduIndia

The 5G demonstrations in a business has a significant role in today’s fast-moving *** in 5G,drives a wireless system intended at an enormously high data rate,lower energy,low latency,and *** this reason,routing protocols of MANET have the possibility of being fundamentally flexible,high performance,and *** 5G communication aims to afford higher data rates and significantly low Over-The-Air *** through supplementary ACO routing processes,a security-aware,fuzzy improved ant colony routing optimization protocol is proposed in *** goal is to develop aMANET routing protocol that could provide a stable packet transmission ratio,less overhead connectivity,and low end-to-end latency in shared standard scenarios and attack *** demonstrates effective results with hybrid architecture and proved to be effective than other state-of-the-art routing protocols of MANETs,like AODV,its routing organization implemented through Optimized Fuzzy based ACO Algorithm for ***-wavelengths are required to perform a significant role in *** research proposed to test the efficiency of MANET consisting of only mmWave User *** reduced packet transmission loss of UEs withmmWave,meaning well-transmitted SNR leads directly to a better packet delivery *** verify results,simulation using the NS-3 simulator mmWave module is used.

关键词： 5G attacks D2D communications MANET mmWave security

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Workflow as a Service Broker in Cloud Environment: A Systematic Literature Review

arXiv

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arXiv 2025年

作者： Abrishami, Saeid Zandi, Faridreza Momtaz Nourbakhsh, Alireza Department of Computer Engineering Faculty of Engineering Ferdowsi University of Mashhad Mashhad Iran Departement of Control and Computer Engineering Politecnico di Torino Torino Italy

Cloud computing has emerged as a promising platform for running scientific workflows across various domains. Scientists can take advantage of different cloud service models, such as serverful or serverless, to execute workflows based on their specific requirements, along with diverse pricing models like on-demand, reserved, or spot instances to reduce execution costs. However, the challenge of selecting appropriate resources and pricing models, coupled with the orchestration and scheduling of workflow tasks, creates significant complexity for users. To mitigate this burden, Workflow as a Service (WaaS) brokers have been introduced to facilitate workflow execution. In recent years, numerous studies have been published, either directly or indirectly related to this research area, highlighting the need for a comprehensive and systematic review of WaaS brokers to identify key trends and challenges in this field. In this paper, we conduct a Systematic Literature Review (SLR) on WaaS brokers within cloud environments. The SLR employs a thorough 3-tier strategy (database search, backward snowballing, and forward snowballing) to answer five research questions. A total of 74 high-quality articles, published in 43 prestigious venues, are analyzed to derive a taxonomy based on the architecture of WaaS brokers. The articles are classified and surveyed according to this taxonomy, and future research directions for the design and implementation of WaaS brokers are explored. This study provides valuable insights for researchers and developers, helping them identify major trends and issues in the field of WaaS brokers. © 2025, CC BY.

关键词： Cloud platforms

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CNNs in Crop Care: A Comparative Analysis of Tomato Disease Detection Models 2

CNNs in Crop Care: A Comparative Analysis of Tomato Disease ...

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2nd International Conference on Cyber Resilience, ICCR 2024

作者： Ali, Ali M Nashwan, Shadi Al-Qerem, Ahmad Aldweesh, Amjad Alauthman, Mohammad Elgamal, Zenab Almomani, Ammar AlAhliyya Amman University Faculty Of Engineering Communications And Computer Engineering Department Amman19328 Jordan Faculty Of Information Technology Cybersecurity Department Amman11831 Jordan Zarqa University Faculty Of Information Technology Computer Science Department Zarqa13110 Jordan College Of Computing And It Shaqra University Shaqra Saudi Arabia University Of Petra Faculty Of Information Technology Department Of Information Security Amman Jordan School Of Computing Skyline University College University City Of Sharjah Sharjah United Arab Emirates School Of Computing Skyline University College Sharjah United Arab Emirates AlHuson University College AlBalqa Applied University I.T. Department Irbid Jordan

ISBN: (纸本)9798350394962

Timely and accurate detection of plant diseases is critical for sustainable crop production. This paper presents a comparative analysis of convolutional neural network (CNN) models for automated tomato leaf disease detection, including VGG16, VGG19, AlexNet and Google Net. A dataset of tomato leaf images with multiple disease types was utilized to train and test the performance of each CNN architecture. Our results demonstrate that the VGG16 model achieved the highest accuracy of 99.38% in classifying tomato leaf diseases. Compared to AlexNet and VGG19 models which obtained 98.67% and 99.29% accuracy respectively, the superior performance of VGG16 highlights its suitability for deploying robust tomato disease detection systems to enable prompt disease control interventions. Our work provides valuable insights on harnessing deep learning for agricultural disease surveillance, allowing farmers and agronomists to identify crop infections early and implement timely management practices to reduce yield losses. © 2024 IEEE.

关键词： Convolutional neural networks

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Type II Fuzzy Logic Based Cluster Head Selection for Wireless Sensor Network

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computers, Materials & Continua 2022年第1期70卷 801-816页

作者： J.Jean Justus M.Thirunavukkarasan K.Dhayalini G.Visalaxi Adel Khelifi Mohamed Elhoseny Department of Computer Science&Engineering St.Joseph’s College of EngineeringChennai600119India School of Computing Science and Engineering Galgotias UniversityUttar Pradesh203201India Department of Electrical and Electronics Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Computer Science&Engineering Bharath Institute of Higher Education and ResearchChennai600073India Department of Computer Science and Information Technology Abu Dhabi UniversityAbu Dhabi59911United Arab Emirates College of Computer Information Technology American University in the EmiratesDubaiUnited Arab Emirates Faculty of Computers and Information Mansoura UniversityEgypt

Wireless Sensor Network(WSN)forms an essential part of *** is embedded in the target environment to observe the physical parameters based on the type of *** nodes inWSN are constrained by different features such as memory,bandwidth,energy,and its processing *** WSN,data transmission process consumes the maximum amount of energy than sensing and processing of the ***,diverse clustering and data aggregation techniques are designed to achieve excellent energy efficiency in *** this view,the current research article presents a novel Type II Fuzzy Logic-based Cluster Head selection with Low Complexity Data Aggregation(T2FLCH-LCDA)technique for *** presented model involves a two-stage process such as clustering and data ***,three input parameters such as residual energy,distance to Base Station(BS),and node centrality are used in T2FLCH technique for CH selection and cluster ***,the LCDA technique which follows Dictionary Based Encoding(DBE)process is used to perform the data aggregation at ***,the aggregated data is transmitted to the BS where it achieves energy *** experimental validation of the T2FLCH-LCDAtechnique was executed under three different scenarios based on the position of *** experimental results revealed that the T2FLCH-LCDA technique achieved maximum energy efficiency,lifetime,Compression Ratio(CR),and power saving than the compared methods.

关键词： Clustering data aggregation energy consumption cluster head selection wireless sensor networks

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Climate Change Analysis Using Machine Learning 3

Climate Change Analysis Using Machine Learning

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3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Sharma, Dolly Gupta, Pawan Rawat, Gourav Kumar, Sharad Malik, Suraj Bansal, Nidhi School of Computing Department Graphic Era Hill University Haldwani India Biet Jhansi Dr. A. P. J. Abdul Kalam Technical University Faculty of Information Technology Lucknow India School of Engineering and Technology Sharda University Department of Computer Science & Engineering Greater Noida India Biet Jhansi Dr. A. P. J. Abdul Kalam Technical University Faculty of Computer Science & Engineering Lucknow India Iimt University Department of Computer Science and Engineering Meerut India Nagpur Campus Pune India

ISBN: (纸本)9798331518592

More analysis is required day to day due to the frequent changes in the weather. Every second the subject needs accurate analysis. This research paper is suggesting a useful technique for analysis using machine learning classification. Dynamic change occurs frequently in this scenario as the real-time application needs to get the process within the machine for accurate output. Accuracy is also a constraint for the situation. The dataset designed based on the selected location is divided by the number of zones, only then the analysis is done for processing to show the result. Sometimes an area is also restricted due to heavy disasters. Due to this care, the problem is divided into the sample area and classification is applied. The results generated by this research paper can show the optimal solution for the determined scenario. © 2024 IEEE.

关键词： Adversarial machine learning

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