A Study on Image Processing Using Artificial Neural Networks in Civil Engineering

Alexandrina-Elena Andon, G. Covatariu
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Abstract

Abstract For the last five years, image processing using artificial neural networks (ANN) got several researchers interested in the field of Civil Engineering. As the artificial neural network, which consists of several neurons may not be able to extract features from the image due to the required computing power, the Convolutional Neural Network (CNN) was created. CNN is a machine learning algorithm that uses the image as input, attributing the importance of different aspects (objects in the image) to allow their differentiation. The results recorded in Civil Engineering domain show a real success.
基于人工神经网络的土木工程图像处理研究
近五年来,利用人工神经网络(ANN)进行图像处理引起了土木工程领域许多研究者的兴趣。由于计算能力的限制,由多个神经元组成的人工神经网络可能无法从图像中提取特征,因此创建了卷积神经网络(Convolutional neural network, CNN)。CNN是一种机器学习算法,它使用图像作为输入,赋予不同方面(图像中的物体)的重要性,以允许它们区分。在土木工程领域记录的结果显示了真正的成功。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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