fieldid E-Thesis & Research สถาบันเทคโนโลยีไทย-ญี่ปุ่น
สืบค้น:

เขตข้อมูล ข้อมูล
บทคัดย่อ
PERFORMANCE ANALYSIS OF IMAGE CLASSIFICATION BETWEEN EDGE AND CLOUD COMPUTING : Image classification has become a major application in the AI era for connecting the physical and digital worlds. However it requires intensive graphic processing power. IoT and Edge Computing have become popular approaches for distributing and offloading the workload from the cloud to the edge. Many edge devices are powered by an energy-efficient processor that cant execute intensive workloads but some may be able to. In this thesis we studied the overview of image classification implementation on edge and cloud computing and analyzed the performance to reveal the opportunity to implement a proper system architecture. The edge and cloud computing environments studied in this paper are a smartphone a personal computer and a cloud GPU instance with sample applications to simulate real-world scenarios. The performance is based on the datasets and the processing environment comprising three factors: ML runtime hardware and network. Resulting in six factors: inference time end-to-end execution time (including network delays) accuracy confidence score resource usage and data transfer.
ผู้แต่ง
Natthasak Vechprasit
ประเภทสิ่งพิมพ์
Thesis (MIT) 2024
เลขหน้า
181
หัวเรื่อง
Information Technology--Thesis
หัวเรื่อง
Thai-Nichi Institute of Technology.Information Technology--Thesis
เอกสารฉบับเต็ม
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