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Enhancing Accuracy and Efficiency in Diabetic Retinopathy Detection: A Deep Learning Framework for Fundus Image Analysis 1

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3rd International Conference on Advanced Computing and Intelligent Technologies, ICACIT 2023

作者： Tayal, Mahima Singh, Jagendra Kumar, Vinish School of Computer Science Engineering and Technology Bennett University Greater Noida India Department of Computer Science Engineering Raj Kumar Goel Institute of Technology AKTU Lucknow Ghaziabad India

ISBN: (数字)9789819719617

ISBN: (纸本)9789819719600

The present research investigates the challenge of accurately and efficiently diagnosing diabetic retinopathy using a deep learning architecture. Our research is based on a sizable dataset of 54,325 fundus images that have been meticulously classified as diabetic retinopathy (DR) positive or negative by medical professionals. The dataset is carefully split into training and validation subsets, with 80% designated for training and 20% for validation, to ensure the robustness of model performance. Convolutional neural networks (CNN), artificial neural networks (ANN), support vector machines (SVM), recurrent neural networks (RNN), and k-nearest neighbors (KNN) are just a few of the machine learning models whose diagnostic performance we examine. CNN came out on top with a precision rate of 98.66% and excellent standards for recall, precision, and F1 score. The results of this study have the potential to significantly improve patient care and treatment by allowing for a quick and precise identification of diabetic retinopathy. The outcomes also demonstrate how medical image processing and diagnosis can be revolutionized by deep learning frameworks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Image enhancement

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Generative AI in Focus : A Comprehensive Review of Leading Models Across Modalities 4

Generative AI in Focus : A Comprehensive Review of Leading M...

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4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： Aishwarya, S. Selvamurugan, C. Parthiban, K.G. Nathan, B. Manoj Prabhakar, J. Mohamed Noordeen, A. Sri Eshwar college of Engineering Department of Computer Science and Engineering Coimbatore India Dhaanish Ahmed Institute of Technology Department of Science and Humanities Coimbatore India Dhaanish Ahmed Institute of Technology Department of Biomedical Engineering Coimbatore India Dhaanish Ahmed Institute of Technology Department of Computer Science and Engineering Coimbatore India Dhaanish Ahmed Institute of Technology Department of Artificial Intelligence & Data Science Coimbatore India

ISBN: (数字)9798331529635

ISBN: (纸本)9798331529635

GenAI has revolutionized the generation of realistic and imaginative data in ways that were previously beyond the capabilities of other machine learning algorithms. This area is rapidly gaining traction, with extensive research currently underway to advance it further. The most recent EY Reimagining Industry Futures Study highlights the generative AI (GenAI) to be a pivotal technology. The surge in GenAI's prominence can largely be attributed to advancements in deep neural networks, hardware technology such as GPUs and increased availability of data. This research study reviews the most popular GenAI models, spanning text, image, and audio modalities. This study provides a comparative analysis of various models, serving as a comprehensive resource for understanding the functionality and efficiency of the top GenAI models available today. © 2024 IEEE.

关键词： Generative adversarial networks

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Cloud-Based Secure Vehicular Navigation System: Ensuring Privacy and Security in Intelligent Transportation

Cloud-Based Secure Vehicular Navigation System: Ensuring Pri...

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2023 IEEE International Conference on Electrical, computer and Energy Technologies, ICECET 2023

作者： Lama, Radhika Singh, Sohit Kumar Karmakar, Sandip National Institute of Technology Computer Science and Engineering Durgapur India

ISBN: (纸本)9798350327816

The rapid advancement in intelligent navigation systems has revolutionized the driving experience and significantly bolstered roadway safety. However, one of the fundamental challenges is to preserve the security of the navigation system. Therefore in this paper, we have addressed the vulnerabilities and threats of navigation systems and provided security against potential cryptographic attacks. Our research not only focuses on identifying and addressing these vulnerabilities but also offers insights into the broader implications of enhancing security in this domain. The performance evaluation and effectiveness of the proposed protocol have been evaluated using the AVISPA tool for security analysis, MIRACL libraries for computational cost, and comparative performance evaluations of the proposed protocol with existing works. The outcomes of the proposed protocol with existing related work show that the former offers improved security and computational efficiency. © 2023 IEEE.

关键词： Authentication Navigation system Privacy Security Vehicular technology

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Real-Time Multi-Lingual Hate and Offensive Speech Detection in Social Networks Using Meta-Learning 38

Real-Time Multi-Lingual Hate and Offensive Speech Detection ...

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38th IEEE Region 10 Conference, TENCON 2023

作者： Prasad, Deepak Kadambari, K.V. Mukati, Raghav Singariya, Sunny National Institute of Technology Computer Science and Engineering Warangal India

ISBN: (纸本)9798350302196

A rapid increase in users on social media has given rise to a vast amount of user-generated content, including hate speech and offensive language. Such content can have serious negative consequences, ranging from psychological harm to inciting violence and discrimination. Existing studies have explored different deep learning and Natural language processing (NLP) methods to perform hate speech detection, and these solutions have yielded significant performance. Most existing solutions are limited to detecting hate speech only in English with less focus on content generated in other languages, particularly in low-resource or regional languages. The goal of this paper is to address this challenge of hate speech detection for low-resource languages and propose a tool that could provide a real-time prediction for social media posts. In this study, the main focus was on English, Hindi, Hinglish, Bengali, and Marathi languages which are commonly used in social media platforms in India. A meta-learning-based model was employed to perform hate speech detection in these languages. The proposed method helps to overcome the limitation of data scarcity and provides fast adaptation to an unseen target language. Extensive experiments were conducted on datasets comprised of different regional languages spoken in India. Accuracy, Precision, recall, and F1-score metrics are used to evaluate the model's performance. The results show that when the dataset size is small, meta-learning-based models perform better than traditional fine-tuned language models. © 2023 IEEE.

关键词： Speech recognition

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Optimization of Traffic System using Adaptive Response First Come First Serve

Optimization of Traffic System using Adaptive Response First...

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Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT), International Conference on

作者： Amutha S Dhruv Singh Shashank Shekhar Singh Anant Gupta Jhandial Kunal Krishna School of Computer Science and Engineering Vellore Institute of Technology Chennai India School of Electronics and Communication Engineering Vellore Institute of Technology Chennai India

ISBN: (数字)9798331540685

ISBN: (纸本)9798331540692

In this period of urbanization and adding vehicular traffic, the optimization of business operation systems is consummate to insure both the effectiveness of transportation networks and the safety of commuters. This exploration paper explores the operation of deep literacy ways to revise the field of business operation. By employing the power of deep learning, sensors and timers, our study aims to develop innovative results that ameliorate the delicacy, rigidity, and real- time responsiveness of business control systems. The primary focus of this exploration is to design a comprehensive deep literacy-grounded business operation system that incorporates colorful data sources. By assaying vast quantities of miscellaneous data, the system will acclimatize to dynamic business conditions and offer real- time perceptivity for effective business inflow operation, accident discovery, and traffic relief. The exploration will also explore the integration of machine literacy algorithms for intelligent business signal control, prioritizing green light allocation grounded on real- time demand and business viscosity. The proposed deep literacy result aims to significantly reduce business traffic, minimize trip times, and enhance overall road safety by furnishing optimized business operation strategies. The exploration will concentrate on the practical perpetration of the system in real- world business scripts, with the eventuality to gauge and acclimatize to colorful civic surroundings. This exploration bid seeks to lay the foundation for a future in which business systems seamlessly acclimatize to evolving business patterns, creating safer, more effective transportation networks, and contributing to a sustainable and intelligent civic ecosystem. The proposed dynamic signal control logic is 83.33 % more efficient in utilizing green time compared to the traditional fixed-time system. Estimated reduction in wasted green time is 25%.

关键词： Viscosity Soft sensors Transportation Traffic control Safety Resource management Vehicle dynamics

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Blockchain Ballotbox: Empowering Democracy Through Tamper-Proof E-Voting 3

Blockchain Ballotbox: Empowering Democracy Through Tamper-Pr...

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3rd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Madhuri, A. Lakshmi, Patnala Rajya John, Patchala Ganesh, Tadapaneni Asma, Shaik Nahila, Pathan PVP Siddhartha Institute of Technology Computer Science and Engineering India

ISBN: (纸本)9798350343632

Election administration has undergone a revolution as a result of the development of digital technology, with electronic voting (eVoting) systems emerging as a significant and ground-breaking replacement for the conventional paper-based procedures. Due to its potential to increase security, transparency, and voter confidence in the electoral process, the integration of blockchain technology into eVoting systems has attracted a lot of attention in this context. In order to address the inherent difficulties and weaknesses prevalent in conventional voting systems, this research offers an electronic voting system (eVoting system) that makes use of blockchain technology's capabilities. The suggested system makes use of the core characteristics of blockchain, such as decentralization, immutability, and cryptographic security, to provide a robust and open platform for the collection and tabulation of votes. This eVoting system's noteworthy characteristics include real-time result verification, anonymous and tamper-proof vote recording, and secure voter authentication. Blockchain's distributed ledger technology makes sure that every vote is recorded in a way that is transparent, verifiable, and immune to manipulation - all while preserving the voter's privacy. Additionally, the use of smart contracts in this system automates a number of voting-related tasks, doing away with the need for middlemen and improving the effectiveness of the overall election process. In summary, incorporating blockchain technology into electronic voting has the potential to revolutionize the electoral landscape by introducing unprecedented levels of security and transparency. By facilitating secure and streamlined remote voting while preserving the integrity of the process, this blockchain-powered eVoting system seeks to strengthen democratic practices and instill confidence in the electoral process in our digital era. © 2023 IEEE.

关键词： Blockchain technology Decentralization Digital technology Election Administration Immutability Security Transparency

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Data Hide Security Using Image Object

Data Hide Security Using Image Object

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2023 IEEE International Students' Conference on Electrical, Electronics and computer science, SCEECS 2023

作者： Tiwari, Pintu Sahare, Tanmay Mahajan, Himanshu Kanojiya, Isha Talekar, Dhanshree Lohe, Prasanna Computer Science Engineering Jhulelal Institute of Technology Nagpur India

ISBN: (纸本)9798350398748

The records leak of touchy facts on structures has a critical chance to company facts protection. Statistics display that the mistaken encryption of documents and communications because of human mistakes is one of the main reasons for records loss. The fast improvement of facts through that made it simpler to ship the facts correctly and quicker to the vacation spot. There are many transmission media to switch the facts to vacation spots like e-mails;at the identical time, its miles can be simpler to adjust and misuse the treasured records through hacking. In order to securely transmit information to its destination without any alterations, there are various techniques such as cryptography and steganography that can be used. Steganography refers to the technique of concealing a message or information within another file, text, or media, in a manner that makes it undetectable to those who are not privy to its existence or significance.. By using steganography, it is possible to covertly transmit information without drawing attention to the fact that it is being transmitted. Current developments prefer the usage of virtual photo documents as the quilt report to cover any other virtual reportthat consists of the name of the game message or records This paper the usage of k-means and encryption set of rules wherein clustered the facts the usage of a clustering set of rules after which the output of the clustering has then hidden the usage of photo steganography to offer a protection layer to that file. © 2023 IEEE.

关键词： Cryptography

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A Comprehensive Study on Advancements in Text Mining and Natural Language Processing

A Comprehensive Study on Advancements in Text Mining and Nat...

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Emerging Research in Computational science (ICERCS), International Conference on

作者： Sarthak Mahire U K Balaji Saravanan Murali M Prabakaran N School of Computer Science and Engineering Vellore Institute of Technology Vellore India Department of Computer Science and Engineering Knowledge Institute of Technology Salem India Department of Information Technology Sona College of Technology Salem India

ISBN: (数字)9798331534967

ISBN: (纸本)9798331534974

Text mining and Natural Language Processing (NLP) have witnessed significant advancements in recent years, driven by the increasing availability of unstructured data and the development of sophisticated machine learning models. This review explores the evolution of text mining and NLP, highlighting the transition from rule-based systems to modern deep learning approaches. This paper reviews various techniques and its impact across various domains. Challenges such as data bias and model interpretability still remain. The paper also discusses future directions, emphasizing the need for fair, interpretable and sustainable NLP systems. This paper aims to provide insights into the current state of text mining and NLP, the challenges faced and potential pathways for future research.

关键词： Text mining Training Technological innovation Reviews Scientific computing Focusing Medical services Natural language processing Data models Multilingual

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A Unified Deep Learning Model for Morse Detection and Recognition 14

A Unified Deep Learning Model for Morse Detection and Recogn...

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14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Bharati Asha, T. Maya, B.S. Bangalore Institute of Technology Computer Science and Engineering Bangalore India

The 21st century has supported advancements in authentication, authorization, and security technology. The usage of personal identifying numbers (PIN) for user security and authentication is commonplace. We choose to use a different approach these days, specifically PIN authentication using a hands-free gaze-basedPIN entry method, because PIN numbers can now be easily cracked. This study intends to provide a framework for setting passwords that uses an eye blink and morse code and aids in the development of safe, private accounts that only authorized users can access. The term "gaze-based authentication" refers to the process of tracking the eye region over time by locating it in successive image frames. The password will be authenticated using morse code, Dashes and dots are used to symbolize the integers. The model will be displayed as a real-time application for eye recognition and tracking for both gaze-based PIN entry and PIN detection using a smart camera. © Grenze Scientific Society, 2023.

关键词： Authentication

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An Enhanced X-Ray Image Classification Model Using Deep Convolutional Neural Networks

SSRN

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SSRN 2023年

作者： Mohan, Suresh Narayan, Subhashini School of Computer Science and Engineering Vellore Institute of Technology Vellore India School of Information Technology and Engineering Vellore Institute of Technology Vellore India

The purpose of this research is to present a unique artificial intelligence model for image processing by leveraging data cleaning and optimization techniques in a deep convolutional neural network. This novel trifecta of methods has the potential to improve the performance of deep neural networks in image processing. Priority was given to the often-overlooked and inadequate data cleaning and optimization stages required when constructing a deep neural network. We were able to get positive outcomes by employing this strategy. We put this conceptual framework to the test by comparing the chest X-rays of people with and without pneumonia to look for commonalities. Several performance metrics, including precision, recall, and F1-score, were enhanced, and the true positives and true negatives were both improved. The accuracy improved, and we saw a notable enhancement while employing our proposed framework. All things considered, the outcomes imply that our framework provides superior results without compromising any performance indicators. © 2023, The Authors. All rights reserved.

关键词： Image classification

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