Evaluating Convolutional Neural Network Architecture for Historical Topographic Hardcopy Maps Analysis: A Study on Training and Validation Accuracy Variation

Evaluating Convolutional Neural Network Architecture for Historical Topographic Hardcopy Maps Analysis: A Study on Training and Validation Accuracy Variation

Convolutional Neural Networks (CNN) are widely used for image analysis tasks, including object detection, segmentation, and recognition. Given the advanced capability, this study evaluates the effectiveness and performance of CNN architecture for analysing Historical Topographic Hardcopy Maps (HTHM)...

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Bibliographic Details
Published in:PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY
Main Authors: Jaafar, Saiful Anuar; Rasam, Abdul Rauf Abdul; Diah, Norizan Mat
Format: Article
Language:English
Published: UNIV PUTRA MALAYSIA PRESS 2024
Subjects:
Science & Technology - Other Topics
Online Access:https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-recordWOS:001347973100001

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