دورية أكاديمية

Distributed System for MeshNet

التفاصيل البيبلوغرافية
العنوان: Distributed System for MeshNet
المؤلفون: Gaggenapalli, Pratyush Reddy
المصدر: Computer Science Theses
بيانات النشر: ScholarWorks @ Georgia State University
سنة النشر: 2024
المجموعة: Scholar Works @ Georgia State University
مصطلحات موضوعية: MeshNet, Convolutional Neural Network, brain tissue segmentation, medical image analysis, distributed learning, resource optimization
الوصف: This thesis explores the integration of Meshnet models with distributed learning techniques to enhance MRI brain scan analysis, with a focus on optimizing brain tissue segmentation while maintaining secure distributed systems. Through refining Meshnet's architecture and training strategies, the goal is to enhance accuracy in identifying brain segmentations. Distributed learning strategies, particularly centralized aggregation, are investigated to enable collaborative model training while ensuring data privacy. Additionally, Coinstac is integrated for secure gradient aggregation from diverse nodes, facilitating collaborative analysis without compromising confidentiality. Implementation of a serverless architecture using public clouds extends global accessibility while upholding robust security measures. The primary aim is to empower professionals with advanced tools for collaborative research.
نوع الوثيقة: text
وصف الملف: application/pdf
اللغة: unknown
العلاقة: https://scholarworks.gsu.edu/cs_theses/113Test; https://scholarworks.gsu.edu/context/cs_theses/article/1117/viewcontent/Gaggenapalli_Pratyush_Reddy_202405_MS.pdfTest
DOI: 10.57709/36919146
الإتاحة: https://doi.org/10.57709/36919146Test
https://scholarworks.gsu.edu/cs_theses/113Test
https://scholarworks.gsu.edu/context/cs_theses/article/1117/viewcontent/Gaggenapalli_Pratyush_Reddy_202405_MS.pdfTest
رقم الانضمام: edsbas.6C6CF676
قاعدة البيانات: BASE