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)...
Published in: | Pertanika Journal of Science and Technology |
---|---|
Main Author: | Jaafar S.A.; Rasam A.R.A.; Diah N.M. |
Format: | Article |
Language: | English |
Published: |
Universiti Putra Malaysia Press
2024
|
Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85208607925&doi=10.47836%2fpjst.32.6.11&partnerID=40&md5=a58973072175fda1b4f5ca0056f130cd |
Similar Items
-
Evaluating Convolutional Neural Network Architecture for Historical Topographic Hardcopy Maps Analysis: A Study on Training and Validation Accuracy Variation
by: Jaafar, et al.
Published: (2024) -
THE ROLE OF GEOSPATIAL ARTIFICIAL INTELLIGENCE (GEOAI) IN SMART BUILT ENVIRONMENT MAPPING: AUTOMATIC OBJECT DETECTION OF RASTER TOPOGRAPHIC MAPS IN MALAYSIA
by: Jaafar S.A.; Abdul Rasam A.R.; Sadek E.S.S.M.; Diah N.M.
Published: (2024) -
Evaluating the Distance Impact to the Scanning Topographic Object with the 3D Point Cloud Resolution
by: Ghazali R.; Razali M.H.; Ghani M.N.A.; Rasam A.R.A.
Published: (2021) -
Comprehensive Analysis of UAV Flight Parameters for High Resolution Topographic Mapping
by: Muhammad M.; Tahar K.N.
Published: (2021) -
A Review on Deep Convolutional Neural Network Architectures for Medical Image Segmentation
by: Awang Mustapa N.H.; Mat Som M.H.; Basaruddin K.S.; Megat Ali M.S.A.
Published: (2022)