Automated recognition of asphalt pavement crack using deep convolution neural network / Nor Aizam Muhamed Yusof ...[et al.]
Pavement distress results in huge predicament such as environmental pollution, traffic congestion, accident and mental health. It can be classified into cracking, potholes rutting and ravelling, however cracking is the most prevalent damage on asphalt pavement. Effective and efficient pavement maint...
Сохранить в:
Главные авторы: | Muhamed Yusof, Nor Aizam (Автор), Osman, Muhammad Khusairi (Автор), Mohd Noor, Mohd Halim (Автор), Md Tahir, Nooritawati (Автор), Ibrahim, Anas (Автор), Mohd Yusof, Norbazlan (Автор) |
---|---|
Формат: | |
Опубликовано: |
Universiti Teknologi MARA,
2019-12.
|
Предметы: | |
Online-ссылка: | Link Metadata |
Метки: |
Добавить метку
Нет меток, Требуется 1-ая метка записи!
|
Схожие документы
-
Consensus and source properties of Malaysian aggregates for superior performing asphalt pavements / Juraidah Ahmad, Mohd Yusof Abdul Rahman and Zainab Mohamed
по: Ahmad, Juraidah, и др.
Опубликовано: (2008) -
Flexible pavement crack's severity identification and classification using deep convolution neural network / A. Ibrahim ...[et al.]
по: Ibrahim, A., и др.
Опубликовано: (2021) -
Advances in Asphalt Pavement Technologies and Practices
Опубликовано: (2022) -
Artificial intelligence system for detection and classification of flexible pavement crack's severity / Anas Ibrahim ... [et al.]
по: Ibrahim, Anas, и др.
Опубликовано: (2020) -
Investigasi Karakteristik Rap Reclaimed Asphalt Pavement) Artifisial
по: Pramudyo, Cahyo, и др.
Опубликовано: (2013)