Deep transfer learning-based vehicle classification by asphalt pavement vibration

Evaluation of Asphalt Pavement Interface

Deep Transfer Learning Ensemble for Classification

Transfer learning algorithms typically assume that the training data and the test data come from different distribution. It is better at adapting to learn new tasks and concepts more quickly and accurately by exploiting previously gained knowledge. Deep Transfer Learning (DTL) emerged as a new paradigm in transfer learning in which a deep model offer greater flexibility in extracting high-level...

An Introduction to Tire/Pavement Noise of Asphalt Pavement

1.0 Introduction ..........................................................................................................................................................2 2.0 Relevant Topics in Sound and Acoustics ............................................................................................................... 2.1 Sound...............................................................

Exploring Deep Learning and Transfer Learning for Colonic Polyp Classification

Recently, Deep Learning, especially through Convolutional Neural Networks (CNNs) has been widely used to enable the extraction of highly representative features. This is done among the network layers by filtering, selecting, and using these features in the last fully connected layers for pattern classification. However, CNN training for automated endoscopic image classification still provides a...

Investigation of Clay Balls in Asphalt Pavement

Clay ball is a pavement surface defect which refers to a clump in which clay or dirt is 8 mixed with hot asphalt mixture. Clay ball is typically caused by a combination of aggregate 9 contamination of clay or soil, high aggregate moisture, and low production temperature at the 10 asphalt plant. It usually appears a few weeks or months after paving under traffic load, after being 11 liquefied an...