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EvoSTS Forecasting: Evolutionary Sparse Time-Series Forecasting
In each generation of our evolutionary algorithm, a set number of children with the same initial weights are spawned.
A Novel Approach for Deterioration and Damage Identification in Building Structures Based on Stockwell-Transform and Deep Convolutional Neural Network
In this paper, a novel deterioration and damage identification procedure (DIP) is presented and applied to building models.
Influence of image noise on crack detection performance of deep convolutional neural networks
Much research has been conducted on classifying cracks from image data using deep convolutional neural networks; however, minimal research has been conducted to study the efficacy of network performance when noisy images are used.
Application of 2-D Convolutional Neural Networks for Damage Detection in Steel Frame Structures
In this paper, we present an application of 2-D convolutional neural networks (2-D CNNs) designed to perform both feature extraction and classification stages as a single organism to solve the highlighted problems.
Learning Program Embeddings to Propagate Feedback on Student Code
Providing feedback, both assessing final work and giving hints to stuck students, is difficult for open-ended assignments in massive online classes which can range from thousands to millions of students.
