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pro vyhledávání: '"Nor Aizam Muhamed Yusof"'
Autor:
Muhammad Khusairi Osman, Nor Aizam Muhamed Yusof, Nooritawati Md Tahir, Norbazlan Mohd Yusof, Fadzil Ahmad, Anas Ibrahim, Mohaiyedin Idris
Publikováno v:
Civil Engineering and Architecture. 9:58-67
In an image classification system based on deep learning, a training dataset is a set of labelled images and is often composed of a large number of images. Image labelling tool is usually used to facilitate in creating the training dataset used by th
Autor:
Nor Aizam Muhamed Yusof, Muhammad Amiruddin Anuar, K. A. Ahmad, Abdul Rahim Ahmad, Muhammad Khusairi Osman
Publikováno v:
2020 10th IEEE International Conference on Control System, Computing and Engineering (ICCSCE).
Pavement distress refers to the condition of pavement surface in terms of its general appearance. Cracks is a type of pavement distress and commonly occur in a road infrastructure. Crack on a pavement surface shows an early sign of pavement problems
Autor:
Norbazlan Mohd Yusof, Adyda Binti Ibrahim, Muhammad Khusairi Osman, Mohd Halim Mohd Noor, Nor Aizam Muhamed Yusof, N. M. Tahir
Publikováno v:
2018 8th IEEE International Conference on Control System, Computing and Engineering (ICCSCE).
Pavement distress particularly cracks, are the most significant type of pavement distress that has been studied for many years due to the complicated pavement crack condition. The continuous severity of crack can cause a dangerous environment that ma
Autor:
Nor Aizam Muhamed Yusof, Muhammad Khusairi Osman, Norbazlan Mohd Yusof, Adyda Binti Ibrahim, N. Z. Abidin, Mohd Halim Mohd Noor, N. M. Tahir
Publikováno v:
Journal of Physics: Conference Series. 1349:012020
Asphalt cracks are one of the major road damage problems in civil field as it may potentially threaten the road and highway safety. Crack detection and classification is a challenging task because complicated pavement conditions due to the presence o
Autor:
Muhammad Khusairi Osman, R. A. A. Raof, Anas Ibrahim, Nor Aizam Muhamed Yusof, Nor Hazlyna Harun, K. A. Ahmad
Publikováno v:
Indonesian Journal of Electrical Engineering and Computer Science. 14:810
This study presents characterization of cracking in pavement distress using image processing techniques and k-nearest neighbour (kNN) classifier. The proposed semi-automated detection system for characterization on pavement distress anticipated to mi