Ni Vision Development Module 2011 Crack
DOWNLOAD --->>> https://urloso.com/2t9Ef8
Abstract:This paper introduces a research on the use of a new automatic crack detection method based on image processing and deep learning technology. The main objective of the research is to find an automatic crack detection method for pavement cracks with high detection accuracy. The identification of pavement cracks is important for the safety of public. The authors propose a Crack Detection Based on Image Processing and Deep Learning Technology (CrackDFANet) method for pavement crack detection. The CrackDFANet method is realized based on image processing and deep learning technology. The authors build an image dataset which contains data from real road pavement crack images, and split the collected data into training set, validation set, and testing set. Then the authors train and test the model using the training set, and validate the model using the validation set, and finally evaluate the model on the testing set. Based on the model evaluation, the CrackDFANet method obtains an accuracy of 99.1% and a precision of 88.2%. Finally, the authors compare and analyze the performance of the CrackDFANet method with other state-of-the-art crack detection methods in terms of detection accuracy and speed.Keywords: crack detection; pavement crack detection; image processing and deep learning technology; crack identification; object detection; street pavement crack identification
Abstract:The use of deep learning (DL) in civil inspection, especially in crack detection, has increased over the past years to ensure long-term structural safety and integrity. To achieve a better understanding of the research work on crack detection using DL approaches, this paper aims to provide a bibliometric analysis and review of the current literature on crack detection using DL approaches, published between 2010 and 2022. The search from Web of Science (WoS) and Scopus, two widely accepted bibliographic databases, resulted in 165 articles published in top journals and conferences, showing the rapid increase in publications in this area since 2018. The evolution and state-of-the-art approaches to crack detection using deep learning are reviewed and analyzed based on datasets, network architecture, domain, and performance of each study. Overall, this review article stands as a reference for researchers working in the field of crack detection using deep learning techniques to achieve optimal precision and computational efficiency performance in light of electing the most effective combination of dataset characteristics and network architecture for each domain.
visio pro 2011 crack thc the devil (2008) (full movie) hd 720p Download Humble Bundle 5 Download crack serial number for windows 7.rar Pdfani pdf converter lite 5.0.2.85.rar Cognitive Science, Psychoactive Drugs: A Practical Handbook, NANO-QUEST, Ed. 2, Oxford, UK: Blackwell Publishing, 2007. PCI, LLC. It gives back the instruments that he should never have taken away. Download free full movies hd Download free full movies hd Download free full movies hd download free full movies hd 827ec27edc