Concrete Condition Assessment Using Impact-Echo Method and Extreme Learning Machines
نویسندگان
چکیده
منابع مشابه
Concrete Condition Assessment Using Impact-Echo Method and Extreme Learning Machines
The impact-echo (IE) method is a popular non-destructive testing (NDT) technique widely used for measuring the thickness of plate-like structures and for detecting certain defects inside concrete elements or structures. However, the IE method is not effective for full condition assessment (i.e., defect detection, defect diagnosis, defect sizing and location), because the simple frequency spectr...
متن کاملA New Method for Detecting Ships in Low Size and Low Contrast Marine Images: Using Deep Stacked Extreme Learning Machines
Detecting ships in marine images is an essential problem in maritime surveillance systems. Although several types of deep neural networks have almost ubiquitously used for this purpose, but the performance of such networks greatly drops when they are exposed to low size and low contrast images which have been captured by passive monitoring systems. On the other hand factors such as sea waves, c...
متن کاملComputerized Data Interpretation for Concrete Assessment with Air-Coupled Impact-Echo: An Online Learning Approach
Developing efficient Artificial Intelligence (AI)-enabled system to substitute human role in 1 non-destructive testing is an emerging topic of considerable interest. In this study, we propose a novel 2 impact-echo analysis system using online machine learning, which aims at achieving near-human 3 performance for assessment of concrete structures. Current computerized impact-echo systems 4 commo...
متن کاملMetagenomic Taxonomic Classification Using Extreme Learning Machines
Next-generation sequencing technologies have allowed researchers to determine the collective genomes of microbial communities co-existing within diverse ecological environments. Varying species abundance, length and complexities within different communities, coupled with discovery of new species makes the problem of taxonomic assignment to short DNA sequence reads extremely challenging. We have...
متن کاملOutlier Detection Using Extreme Learning Machines Based on Quantum Fuzzy C-Means
One of the most important concerns of a data miner is always to have accurate and error-free data. Data that does not contain human errors and whose records are full and contain correct data. In this paper, a new learning model based on an extreme learning machine neural network is proposed for outlier detection. The function of neural networks depends on various parameters such as the structur...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Sensors
سال: 2016
ISSN: 1424-8220
DOI: 10.3390/s16040447