[PDF][PDF] Predicting the defects in wooden structures by using pre-trained models of Convolutional Neural Network and Image Processing

R Ehtisham, W Qayyum, CV Camp, J Mir… - … Conference on Recent …, 2022 - researchgate.net
Wood is the oldest material used in construction industry and wooden structures are often
exposed to harsh conditions of environment. This exposure lead to deterioration due to …

[PDF][PDF] Detecting cracks with Convolution Neural Network (CNN) with Variable image dataset

W Qayyum, R Ehtisham, C Camp, J Mir… - … Conference on Recent …, 2022 - researchgate.net
Millions of dollars are spent annually to detect damages in demanding infrastructures,
including bridges, roads, and buildings. Natural disasters such as floods and earthquakes …

[PDF][PDF] Timber Defect Identification: Enhanced Classification with Residual Networks.

TH Chun, UR Hashim, S Ahmad - International Journal of …, 2024 - saiconference.com
This study investigates the potential enhancement of classification accuracy in timber defect
identification through the utilization of deep learning, specifically residual networks. By …

Predicting the Characteristics of Defects in Wood Structures Using Image Processing and CNN

A Ahmad, RE ul Hassan, J Mir - … Optimization Applications in …, 2024 - igi-global.com
These defects can occur in the form of cracks, pain deterioration, dampness, etc. due to
mechanical and weathering effects. Crack identification and categorization must be part of …