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2024 IEEE International Conference on Innovation and Novelty in engineering and technology, INNOVA 2024

作者： Math, RajinderKumar M. Dharwadkar, Nagaraj V. Sajjanar, Vijaykumar Deshmukh, M.N. Department of Electronics and Communication Engineering B.L.D.E.A’s V.P. Dr. P.G. Halakatti College of Engineering and Technology Karnataka Vijayapur India Department of Computer Science Central University of Karnataka Kadaganchi Kalaburgi India

ISBN: (纸本)9798331505134

The conventional methods of manual grading of fruits after agricultural harvest have always been laborious, time-consuming, and prone to human errors. In order to speed up the grading process without human intervention, an automatic system is the need of the hour. This research has led to the development a Convolutional Neural Network (CNN) based deep learning technique to provide real-time grading of pomegranate based on its visual features. This automatic grading technique would help farmers in minimizing their efforts and time spent on manual sorting, at the same time ensuring error-free and uniform sorting and packaging of quality fruits that would, in turn, enhance the storage time post packaging. The methodology uses nine pre-trained models to train on a custom pomegranate dataset with twelve grade-quality classes of pomegranates. The grade-quality grading is obtained using the fine-tuning approach in transfer learning, reducing the computational resource requirements and drastically improving inference speed, which is necessary for real-time model deployment scenarios. The results reveal that the fine-tuning of DenseNet-169 model outperformed the other models by achieving highest values of 99.20% and 1 for (Accuracy, Precision, Recall, and F1-score) and AUC, respectively. © 2024 IEEE.

关键词： Convolutional neural networks

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Digital media industry driven by 5G and blockchain technology

Digital media industry driven by 5G and blockchain technolog...

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International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Irfan, B.Md. Raman, Ramakrishnan Praveena, Hirald Dwaraka Senthilkumar, G. Kumar, Ashok Bakhare, Ruhi Department of Information Technology Nalsar University of Law Telengana Hyderabad India Maharashtra Pune India Department of Electronics and Communication Engineering School of Engineering Mohan Babu University Andhra Pradesh Tirupati India Department of Computer Science and Engineering Panimalar Engineering College Tamil Nadu Chennai India Department of Computer Science Rajasthan Banasthali Vidyapith India Dr. Ambedkar Institute of Management Studies and Research Maharashtra Nagpur India

ISBN: (纸本)9781032669663

5G (5 Generation) is maximum providing data per second speed (interval) per second average Megabits per Second (Mbps), can 20 gigabits 100 Mbit peak data rate is more significant than faster 4G. 5G is, have a greater capacity. 5G is to support the business ability by multiplying by 100, has been designed to increase network efficiency. 5G is, have a lower than 4G latency. Focus on sharing content-centric networks face a huge range of content requested to provide in Digital Media. How efficiently and safely protect the information network for the upcoming 5Gage is a problem. 5G mobile networks, contentcentric block chain-based SHA-256 (Secure Hash Algorithm) programs to address the privacy issue. Also, a block chain ledger of features ensures privacy and access control of the supplier. With the help of miners user selected, the author can be maintained for the public ledger’s convenience. The share of low overhead, network delay, and congestion implement green interesting data communications. © 2024 The Author(s).

关键词： Digital storage

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Adaptive Modulation and Coding Policies for Multiple Access Wireless Networks 15

Adaptive Modulation and Coding Policies for Multiple Access ...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Dev, Anoop Ramya, G. Goyal, Shobhit Lodi, M.K. Gawali, Piyush P. Amudha, A. Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai127 India Quantum University Research Center Quantum University India Karnataka Bangalore India Vishwakarma Institute of Technology Department of Computer Engineering Pune India Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore641021 India

ISBN: (纸本)9798350370249

Adaptive modulation and coding policies (AMCPs) are proposed to boost throughput and spectral performance in more than one access Wi-Fi network. These regulations dynamically modify the modulation and coding schemes (MCS) for each user based totally on their respective channel situations, thereby enabling the most utilization of available assets. To this cease, many techniques, together with maximum throughput, minimal throughput, proportional fairness, and pleasant channel, were studied. AMCPs remember average person behaviors, inclusive of the type of provider, arrival price, and packet size, while choosing the best MCS for every user. It allows for efficient, useful resource utilization and extended spectral efficiency. Furthermore, the potential to speedy exchange MCS on the air interface permits for services including adaptive information charge and multimedia streaming with scalability. Thus, implementation of AMCPs in a couple of get right of entry to wireless networks can cause a good sized development in consumer experience and higher gadget utility. © 2024 IEEE.

关键词： Adaptive modulation

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An Improved Fingerprint-based Document Image Retrieval using Multi-resolution Histogram of Oriented Gradient Features

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International Journal of engineering, Transactions A: Basics 2022年第4期35卷 750-759页

作者： Dixit, U.D. Shirdhonkar, M.S. Department of Electronics and Communication Engineering BLDEA's V. P. Dr. P. G. Halakatti College of Engineering & Technology Vijayapura India Department of Computer Science and Engineering BLDEA's V. P. Dr. P. G. Halakatti College of Engineering & Technology Vijayapura India

Recently most of the documents are authenticated by using a latent fingerprint impression. Examples of such documents are property registration, banking transactions, insurance documents, etc. The fingerprint-based document retrieval (FPDIR) has emerged to provide an easier way of accessing, browsing, or searching such document images. This paper proposes efficient fingerprint-based document image retrieval by employing multi-resolution Histogram of Oriented Gradient (HOG) features. The preprocessing technique presented in this paper employs a combination of top-hat and bottom-hat filtering operations to enhance the detected fingerprint image. Multi-resolution HOG features are constructed from horizontal, vertical and diagonal directional components of the enhanced fingerprint image. Finally, a standardized Euclidean distance metric is used as a tool for matching, ranking and retrieval of the document images. The proposed system is assessed by experimenting with a dataset of 1200 images. The precision and recall results obtained using the proposed research work have given an improvement of 8% to 14% in retrieval performance compared to earlier methods. © 2022 Materials and Energy Research Center. All rights reserved.

关键词： Discrete wavelet transforms

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Development of a Comprehensive Deep Learning Framework for Enhanced Detection and Accurate Classification of Renal Cancer

Development of a Comprehensive Deep Learning Framework for E...

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International Conference on Trends in electronics and Informatics (ICEI)

作者： J Bino C. Preethi M. Renukadevi T.K.S Rathish babu S. Kanageswari Leema Nelson Department of Electronics and Communication Engineering St. Joseph's Institute of Technology Department of Computer Science Engineering Sethu institute of technology Department of Computer Science Engineering SRM Institute of Science and technology Ramapuram Chennai Department of computer science and Application Loyola College Chennai Chitkara University Institute of Engineering & Technology Chitkara University Punjab India

ISBN: (数字)9798331544607

ISBN: (纸本)9798331544614

Accurate and early diagnosis of renal cancer is important for the improvement of outcomes in patients; hence, timely intervention has much to do with the effectiveness of treatments and survival rates. While there has been an increase in medical imaging modalities, early detection of renal cancer has become quite plausible, though the complexity introduced in the characteristics of tumors calls for advanced methods for their reliable classification. In this work, a new LSTM+CNN-based model is developed for renal cancer disease detection by integrating sequential learning capability from LSTM networks together with the powerful feature extraction abilities of CNN. The system is designed to improve both the accuracy and efficiency in renal cancer diagnosis based on the medical imaging data using spatial and temporal features. Among these, the proposed LSTM+CNN-based model has turned in better accuracy with quicker processing time and better overall classification performance compared to the state-of-the-art models. The proposed model also allows for the non-invasive, high-precision differentiation of renal tumors into low- and high-grade ones, with a view to early diagnosis and prediction. These results provide a proof of the enormous potentials of deep learning models, especially the LSTM+CNN architecture, toward making renal cancer detection an efficient and practical clinical solution.

关键词： Deep learning Support vector machines Accuracy Computational modeling Predictive models Reliability Medical diagnosis Long short term memory Cancer Tumors

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Virtual and Augmented Reality technology for the Treatment of Mental Health Disorders: An Overview 13

Virtual and Augmented Reality Technology for the Treatment o...

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13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022

作者： Anjali Singh, Gurjinder Kaur Sandhu, Jasminder Department of Computer Science and Engineering Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura India Department of Electronics and Communication Engineering Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura India Department of Computer Science and Engineering Chandigarh University Punjab Mohali India

ISBN: (数字)9781665452625

ISBN: (纸本)9781665452625

Augmented and Virtual Reality plays an important role in the field of medical health science. According to the study of past decades, Human computer interaction helps the patients to recover from their issues very quickly. Virtual Reality is used in several fields nowadays and the study of this paper is in the field of clinical sector. The purpose of using Virtual Reality concepts on the patients is that it helps to change the functioning of the brain and also change the behavior, mood, and perception of the person. For example phobias, and addicted person, when person is in an abnormal situation and their mind is not working properly at that time they need a virtual environment. There is a requirement to show the virtual videos to the patients according to their problems. So to analyze the problem of the patients, use virtual reality concept to check the level of the stress, anxiety, and phobias. © 2022 IEEE.

关键词： Augmented reality

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A Novel Framework Leveraging Adam Optimization Techniques, Coupled with Mask R-CNN Deep Learning Mechanisms for Cervical Cancer Detection System

A Novel Framework Leveraging Adam Optimization Techniques, C...

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Applied Artificial Intelligence and Computing (ICAAIC), International Conference on

作者： G. Saranya C. Sujatha Department of Electronics and Communication Engineering SSM Institute of Engineering and Technology Dindigul Tamil Nadu India Department of Computer Science Engineering SSM Institute of Engineering and Technology Dindigul India

ISBN: (数字)9798350375190

ISBN: (纸本)9798350375206

Cervical cancer remains a significant public health concern, with early detection crucial for successful treatment. Deep learning techniques offer promising avenues for automated cancer diagnosis, and this work explores the potential of the Mask R-CNN model with Adam optimization for cervical cancer detection in colposcopy images. This study aims to develop and evaluate a deep learning system based on Mask R-CNN and Adam optimization for automated detection and segmentation of cervical lesions in colposcopy images. The proposed system utilizes Mask R-CNN, a deep convolutional neural network (CNN) is capable of both object detection and instance segmentation. Pre-trained on the COCO dataset, the model is fine-tuned on a labeled colposcopy image dataset for cervical lesion detection and segmentation. Adam optimization, an efficient gradient descent algorithm, is used to maximize the training process of the model. High accuracy in recognizing and differentiating cervical lesions in colposcopy images is anticipated from the system. The system should demonstrate its ability to perform effectively on unseen data and handle variations in image quality. The proposed system’s performance is evaluated on a separate test dataset using standard metrics like accuracy, sensitivity, specificity, and precision for both lesion detection and segmentation tasks. Additionally, the system’s generalizability and robustness to variations in image quality are assessed. This novel approach has the potential to significantly contribute to the field of cervical cancer diagnosis by providing an automated, accurate, and efficient system for early detection, ultimately leading to better patient outcomes.

关键词： Training Deep learning Image quality Accuracy Sensitivity Transfer learning Lesions

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Development of an Instrumented Glove for the Characterization of Human Wrist Tremor 7

Development of an Instrumented Glove for the Characterizatio...

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7th International Conference on electronics, Communication and Aerospace technology, ICECA 2023

作者： Lakineni, Prasanna Kumar Dhana Sony, J. Sharma, Ruchi Chitra, M. Jose Anand, A. Anchitaalagammai, J.V. GITAM School of Technology Department of Computer Science and Engineering GITAM University Visakhapatnam India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Biomedical Engineering Chennai600062 India JECRC Foundation Department of AI&DS Rajasthan Jaipur302022 India Rajalakshmi Institute of Technology Dept of ECE Tamilnadu Chennai India KCG College of Technology Karapakkam Department of Electronics and Communication Engineering Chennai600097 India Velammal College of Engineering and Technology Department of Computer Science and Engineering Tamilnadu Madurai India

ISBN: (纸本)9798350340600

It is common for human beings to present some diseases and disorders as they age, due to neuromusculoskeletal disorders. One of the problems that can appear is the human tremor. There are numerous strategies for tremor attenuation. Among the most common methods, the use of medications, local surgical procedures, electrical stimulation and the use of active orthoses stand out. In this context, robotic rehabilitation is of interest to science more and more. Among the methods for inhibiting tremor, active orthoses are the most efficient and non-invasive means. With that in mind, and also in terms of their quality of life, studies on orthoses to suppress tremor were carried out. Due to the complexity of the device, the present study aims to develop and evaluate an instrumented glove, properly constructed to characterize human wrist tremor in patients affected with such dysfunction. To this end, the basic operating principle of the active orthosis is presented, seeking to highlight more specifically the instrumented glove with its motion and muscle actuation sensors. © 2023 IEEE.

关键词： Biomedical signal processing

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Comparative Evaluation of Fraud Detection in Online Payments Using CNN-BiGRU-A Approach

Comparative Evaluation of Fraud Detection in Online Payments...

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2023 International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023

作者： Prabhakar, K. Giridhar, M.S. Tatia, Amrita Joshi, Trupti Mandar Pal, Subharun Aswal, Upendra Singh School of Engineering and Technology Cmr University Department of Computer Science and Engineering Bangalore India Lakireddy Bali Reddy College of Engineering Department of Electrical and Electronics Engineering Jntuk Kakinada Andhra Pradesh Mylavaram India Indira School of Business Studies Maharashtra Pune India Indira School of Business Studies Masters of Business Administration Maharashtra Pune India Indian Institute of Technology Jammu Department of Computer Science and Engineering Jammu & Kashmir India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350300857

Online payment systems are now ubiquitous in people's daily lives. However, with this increased convenience comes a new security risk. Due to the nature of cybercrime involving an online payment service, which is often characterized by specialization, diversification, concealment, industrialization, scenario, and cross-regional elements, online payment security is notoriously difficult to implement and maintain. Effective and comprehensive online payment fraud detection is crucial. The first three stages of the proposed technique are preprocessing, feature selection, and model training. Remove Null Value, Data Transform, Resample, and Normalize Data are all preprocessing techniques used to improve the quality of raw data. Feature selection makes use of PCA and IG as a means of analysis. CNN-BiGRU-A is used to train the models after information gain is used to choose relevant features. When compared to the two most common alternatives, BiGRU and CNN, the proposed technique performs better. © 2023 IEEE.

关键词： Principal component analysis

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Investigations on Cyber Security Vulnerability using Distribution Analysis

Investigations on Cyber Security Vulnerability using Distrib...

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2024 IEEE International Students' Conference on Electrical, electronics and computer Science, SCEECS 2024

作者： Andrews, Leo John Baptist Alagappan, Annamalai Sarathkumar, D. Fathima, M. Venkatachary, Sampath Kumar Rajeshkanna, R. Raj, Raymon Antony Botho University Faculty of Engineering and Technology Department of Information Technology Gaborone Botswana Botho University Faculty of Engineering and Technology Department of Network and Infrastructure Management Gaborone Botswana Kongu Engineering College Department of Electrical and Electronics Engineering Tamilnadu Erode District638 060 India Sri Krishna College of Engineering and Technology Department of Computer Science and Business Systems Tamilnadu Coimbatore India Grant Thornton Botswana Plot 50370 Acument Park Fair Grounds Gaborone Botswana Thamirabarani Engineering College Department of Eee Tamil Nadu Tirunelveli627 358 India

ISBN: (纸本)9798350348460

Internet communication is used as a mode of engagement by businesses, organizations, and even nations in a variety of contexts. As a result, both the quantity of data produced and the importance of the information that can be derived from it are growing. Multiple safeguards are required in order to ensure that the accessibility, integrity, and confidentiality of company information and assets are maintained. When it comes to protecting the privacy of a company and its reputation, adopting countermeasures and minimizing the damage caused by irreversible cyberattacks are both very crucial. It is possible to utilize both active and passive attack tactics, as well as social engineering tests, to evaluate the weaknesses of a corporation's cyber security. The identification and ranking of vulnerabilities both play an active part in the process of raising the level of corporate awareness, as well as closing shortfalls and enhancing measures. In this investigation, ethics committee reports and confidentiality agreements were followed in order to do a cyber security vulnerability assessment on seven separate organizations. These organizations represented the governmental sector, the corporate sector, and the civil society. In order to evaluate the effectiveness of the firms' cyber security infrastructures, security scans such as port, web, application-based system and network penetration tests, distributed denial of service attacks, and social engineering were carried out. The Common Vulnerability Scoring System (CVSS) was used in order to change the base score of each institution and to identify the vulnerabilities that were present. Enterprise Networks, Cyber Security Analysis, Cyber Attacks, Penetration, and Vulnerability are some of the Keywords that can be found in this article. © 2024 IEEE.

关键词： cyber analysis Introduction cyber security cyber-attacks vulnerabilities

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