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检索条件"任意字段=5th International Conference on Data Science, Machine Learning and Applications, ICDSMLA 2023"

共 2608 条记录，以下是81-90 订阅

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Applying Transfer learning to Medical Image Classification Tasks 5th

Applying Transfer Learning to Medical Image Classification T...

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5th international conference on data science, machine learning and applications, icdsmla 2023

作者： Gupta, Manali Haripriya, V. Singh, Akhilendra Pratap Yadav, Surendra Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Computer Science & Application Vivekananda Global University Jaipur India

ISBN: (纸本)9789819780426

Transfer studying is a machine learning approach that permits a model to leverage know-how from a previous challenge to boost studying in the following tasks. It's been used increasingly in medical photo classification obligations, allowing area-particular knowledge to be leveraged from current fashions. this method can enhance the overall performance of clinical photograph-type structures and reduce the amount of labeled information required to analyze a brand-new venture. In this paper, we assess the present-day kingdom of switches, getting to know the scientific photo category and the results for clinical picture evaluation. We discuss present switch studying techniques and their influences on the accuracy of medical photo category responsibilities and the challenges related to constructing generalizable fashions. Eventually, we take a look at existing datasets and implementations available for the clinical photo category and factor into promising destiny studies guidelines. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Investigating the Benefits of Multi-Task Transfer learning for Medical Image Segmentation 5th

Investigating the Benefits of Multi-Task Transfer Learning f...

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5th international conference on data science, machine learning and applications, icdsmla 2023

作者： Chandani, Priyanka Jaison, Feon Pandeya, Megha Sharma, Neeraj Noida Institute of Engineering and Technology Uttar Pradesh Noida India Department of Computer Science and Information Technology Jain University Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Electrical Engineering Vivekananda Global University Jaipur India

ISBN: (纸本)9789819780426

Multi-challenge transfer getting to know (MTTL) is a technique utilized in machine studying to improve the performance of one or extra models employing leveraging understanding from associated tasks. this article examines the benefit of MTTLC for medical photo segmentation. they segmented clinical photos with a deep learning model to compare the two, using a multi-mission method rather than only one undertaking. the authors develop a framework to teach two models, one consistent with each task, and explore the usage of MTTLC to refine the second version. the results show that while the single project network can attain proper performance, the MTTLC technique can significantly enhance segmentation accuracy. the results suggest that MTTLC could be a beneficial tool in scientific imaging, and extra research is needed to explore its ability and benefits. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive learning

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Study of Diverse Levels in Digital Forensics and IoT Forensics 5th

Study of Diverse Levels in Digital Forensics and IoT Forensi...

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5th international conference on data science, machine learning and applications, icdsmla 2023

作者： Ammannamma, T. Shalini, Kusuma Usha, Vadde Nageswari, Akula Department of IT G. Narayanamma Institute of Technology and Science Telangana Hyderabad India Department of ECE Chaitanya Deemed to University Telangana Warangal India

ISBN: (纸本)9789819780426

Digital forensics, a vital discipline in cybersecurity and investigations, has expanded to encompass the complexities of the Internet of things (IoT). IoT forensics, dedicated to IoT device and data investigations, presents unique challenges. Digital and IoT forensics encompass multi-tiered levels of investigation, each with its unique challenges and objectives. this paper introduces digital forensics highlights, IoT forensics’ distinctive aspects and provides a concise overview of the different levels of digital and IoT forensics. Each level requires specialized techniques and tools to address resource constraints, diverse data sources, legal compliance, and privacy concerns. As digital and IoT technologies evolve, a comprehensive understanding of these levels is essential for conducting effective investigations and upholding cybersecurity and legal standards. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Cybersecurity

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Investigating the Benefits of Interoperability in 5G-Enabled Health Care Management Models 5th

Investigating the Benefits of Interoperability in 5G-Enabled...

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5th international conference on data science, machine learning and applications, icdsmla 2023

作者： Devrani, Rekha Batra, Raman Gobi, N. Chaudhary, Chetan Department of Computer Science and Engineering Vivekananda Global University Jaipur India Department of Mechanical Engineering Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

Interoperability, or correspondence between at least two programming applications, is a vital improvement in 5G innovation that can have critical ramifications for medical services the executive’s models. the efficiency with which health care professionals can access various patient data points, manage their workflow, and provide higher-quality care is enhanced by software applications’ ability to interact with one another. Furthermore, interoperability can assist with lessening medical services costs, work on understanding results, and work with better correspondence between medical cares suppliers. this paper investigates existing examinations on interoperability and the potential advantages it could bring to 5G Based medical services the executives models. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： 5G mobile communication systems

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A Literature Review on Predictive data Analytics and learning Models in Stock Market Trend Analysis 5th

A Literature Review on Predictive Data Analytics and Learnin...

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5th international conference on data science, machine learning and applications, icdsmla 2023

作者： Kumar, Chanda Raj Manikandan, S. Department of Computer Science and Engineering Annamalai University Tamilnadu Chidambaram India

ISBN: (纸本)9789819780426

In today’s volatile financial landscape, where the stock market presents opportunities and risks, predictive data analytics and learning models have become indispensable tools for analyzing and predicting market trends. this study highlights the significant impact of these advanced tools in deciphering complex market fluctuations. By leveraging machine learning models, the research seeks to develop flexible strategies that utilize pattern recognition and statistical analysis to anticipate potential trends. Predictive data analytics is at the core of this research, serving as a fundamental pillar for extracting actionable insights and making data-driven decisions from vast datasets. the integration of Artificial Intelligence (AI) enhances this process, allowing for a deeper exploration of market complexities, uncovering hidden correlations, and identifying predictive markers that traditional methods might miss. this paper provides a thorough analysis and critical review of previous approaches and methods to make stock market predictions and trends using data analytics and learning techniques. the study examines the strengths and weaknesses of different approaches and discusses potential challenges associated with predicting stock portfolios and stock trend analysis through data analytics and learning techniques. the paper concludes by providing an analysis and outlook on the future direction of Stock Market Trends using data analytics and learning techniques. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Predictive analytics

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Enhancing Multi-crop Disease Prediction Using Convolutional Neural Networks: A Global Perspective 5th

Enhancing Multi-crop Disease Prediction Using Convolutional ...

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5th international conference on data science, machine learning and applications, icdsmla 2023

作者： Garigipati, Nagababu Nivrithi, Bathini ShreshtaReddy, Dachireddy Eesha, Mummaneni Nikitha, Patlavath G. Narayanamma Institute of Technology and Science Telangana Hyderabad India

ISBN: (纸本)9789819780426

Given the recent rate of population expansion, it is anticipated that by 2050, global crop productivity will need to double. Getting this production result is significantly hampered by pests and diseases. It is essential to offer efficient methods for automatically diagnosing, classifying, and foretelling diseases and pests in agricultural crops. machine learning techniques can be applied to the data being worked on to extract information and relationships in order to automate this process. Deep learning techniques are employed in the study, which focuses on the categorization, detection, and pest and disease prediction tasks in the agricultural industry. We seek to advance precision agriculture and smart farming by supporting the development of techniques that will allow farmers to use less pesticides and chemicals while protecting and improving the quality and yield of their crops. We’ll employ image classification method, in which the user uploads a photo of the diseased plant or crop, and the system uses deep learning techniques to identify the disease type. And this disease identification will offer advice on how to treat or avoid that crop. the goal is to create a uniform approach for all features and deliver results for all crops throughout the majority of regions in India that are as accurate as possible. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional Neural Networks Deep learning Image Processing Plant diseases Prediction

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A Comprahensive Analysis of Knowledge Transfer Techniques for Medical Image Segmentation with Deep learning 5th

A Comprahensive Analysis of Knowledge Transfer Techniques fo...

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5th international conference on data science, machine learning and applications, icdsmla 2023

作者： Singh, Vishvendra Jain, Garima Nidhya, M.S. Chaudhary, Chetan Department of Agriculture Vivekananda Global University Jaipur India Noida Institute of Engineering and Technology Uttar Pradesh Noida India Department of Computer Science and Information Technology Jain University Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

this paper aims to comprehensively examine diverse knowledge switch techniques used in scientific photograph segmentation with deep mastery. Specifically, we know the latest advances in transfer, gaining knowledge of model adaptation, first-rate-tuning, and transfer mastering techniques. For each technique, we discuss the motivations, techniques, and demanding situations concerned with their software for medical picture segmentation. Similarly, we discuss a variety of open issues and destiny studies guidelines. Furthermore, we overview present applications of these methods in clinical photograph segmentation. Sooner or later, we provide a complete contrast of these processes based on the evaluation metrics hired in the literature. this paper aims to shed light on the modern state of understanding switch techniques in medical picture segmentation and to provide a roadmap for future research on this unexpectedly evolving field.. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive learning

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Analysis of Applied Cryptography for Secure VoIP Communications 5th

Analysis of Applied Cryptography for Secure VoIP Communicati...

引用

5th international conference on data science, machine learning and applications, icdsmla 2023

作者： P, Anitha Agarwal, Trapty D, Ganesh Anand, Piyush School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bengaluru India Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Navgaon Manduwala Dehradun India

ISBN: (纸本)9789819780426

this paper presents an evaluation of the utility of cryptography for at ease Voice over net Protocol (VoIP) verbal exchange. It covers the fundamentals of secure conversation as well as elements of public key cryptography for at ease authentication and encryption. It also covers the hooked up consultation Protocol (ESP), a protocol utilized in VoIP for encryption and authentication in cozy communications. Subsequently, this paper examines the advantages of the usage of cryptographic techniques in VoIP as well as related safety challenges. the evaluation of the utility of cryptography for comfortable VoIP communications offers a foundation for the assessment of cozy communique protocols in VoIP implementations. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Authentication Protocol

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Prediction of Epileptic Seizures by machine learning and Deep learning Techniques Using sEEG Signals: Review 5th

Prediction of Epileptic Seizures by Machine Learning and Dee...

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5th international conference on data science, machine learning and applications, icdsmla 2023

作者： Sravanthi, Chitirala Santhosh Kumar, B. Jawaharlal Nehru Technological University Anantapur Andhra Pradesh Anantapur Ananthapuramu India Department of Information Technology G. Narayanamma Institute of Technology and Science Hyderabad Shaikpet500104 India G. Pulla Reddy Engineering College Kurnool-518007 Affiliated to Jawaharlal Nehru Technological University Anantapur Andhra Pradesh Ananthapuramu India

ISBN: (纸本)9789819780426

Clinical decision support systems could be transformed by accurate forecasting of high-risk clinical signs, such as epileptic seizures, and new therapeutic approaches for patients. Physiological signals can be continuously recorded as a result to the advancement of pervasive sensor technology, preventing the catastrophic effects of epilepsy. However, the lack of an autonomous early warning system has hampered the development of seizure prediction. the most recent set of research groups electroencephalograph (EEG) clips and separates the clips that represent the commencement of epilepsy. If such seizures were predicted in advance then patients can overcome the injuries and effects, so can lead a smoother life. In spite of years of research, prediction of seizures is challenging. therefore new advancements have been made in ML and DL based algorithms to predict the seizure using scalp EEG (sEEG). © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electroencephalography

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An Effective Prediction of Heart Diseases Using machine learning Techniques 5th

An Effective Prediction of Heart Diseases Using Machine Lear...

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5th international conference on data science, machine learning and applications, icdsmla 2023

作者： Obulesu, O. Yakshitha, Koulampeta Vuyyuru, Sanjana Meenakshi, Tumkur Vaishnavi, Pujala Department of Computer Science and Engineering G. Narayanamma Institute of Technology and Science Telangana Hyderabad India

ISBN: (纸本)9789819780426

the heart plays a crucial role in the survival of living organisms by serving as the central pump that circulates blood throughout the body. Heart disease is often considered one of the most life-threatening conditions in humans due to its significant impact on health and mortality rates. the healthcare sector accumulates massive volumes of healthcare data, but regrettably, much of this valuable information often remains untapped, preventing the industry from uncovering hidden insights that could enhance decision-making processes. Hidden patterns and relationships are often left undiscovered and underutilized. the use of advanced machine learning techniques offers a promising solution to address the complexities involved in predicting heart diseases. It represents a crucial challenge within the realm of clinical data analysis, as accurately identifying and forecasting heart-related conditions is of paramount importance for improving healthcare outcomes. Early prediction of heart attack may save many lives hence preventing these has become more than necessary. machine learning (ML) has the potential to provide highly efficient solutions for decision- making and precise predictive capabilities. In the field of machine learning, there are several classification models such as Logistic Regression, K- nearest neighbors (K-NN), and Support Vector machine (SVM) that have proven effective in achieving the goal of predicting and diagnosing heart diseases. Decision Tree Classifier, in particular, serves as a valuable decision support system for detecting and forecasting heart diseases and heart attacks in individuals by utilizing risk factors associated with heart disease. datasets containing medical parameters play a pivotal role in this process, as they are processed through various machine learning algorithms. these algorithms help uncover correlations among the different attributes present in the dataset using standard machine learning techniques. the overarching aim of t

关键词： Adversarial machine learning

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