The participants consisted of 1122 university students studying at a state university in Turkey. The study used the Revised Study Process Questionnaire (R-SPQ-2F) to assess deep and surface learning approaches and the Fear of Missing Out Scale (FoMOs) to measure FoMO level. The findings indicate...
Deep and surface learning approachHigher Education InstitutionsLearning environmentThe learning environments created in higher education institutions (HEI) are to a large extent not empowering students to meet demands of the workplace. Business management students who are only exposed to direct teaching ...
Online learning, though, asks for the combination of different delivery methodologies to contribute towards the optimization not only of the learning development, but also of deployment costs and time8. In this context, a key-factor that adds value to the quality of the learning experience is the...
Our proposed method is termed DEEP2. DEEP2consists of a learning-powered inverse model that can reconstruct a de-scattered image from only 32 DEEP measurements (instead of 256 in our original work, DEEP). The model architecture is inspired by the UNet but modified to include a self-attention...
内容提示: Deep learning for quality control of surface physiographic f i eldsusing satellite Earth observationsTom Kimpson 1 , Margarita Choulga 2 , Matthew Chantry 2 , Gianpaolo Balsamo 2 , Souhail Boussetta 2 , Peter Dueben 2 ,and Tim Palmer 11 Department of Physics, University of Oxford,...
Firstly, a multi-task deep CNN model is constructed for jointly learning hippocampal segmentation and disease classification. Then, we construct a 3D Densely Connected Convolutional Networks (3D DenseNet) to learn features of the 3D patches extracted based on the hippocampal segmentation results for ...
Deep Learning - UWaterlooby Prof. Ali Ghodsi at University of Waterloo (2015) Statistical Machine Learning - CMUby Prof. Larry Wasserman Deep Learning Courseby Yann LeCun (2016) Designing, Visualizing and Understanding Deep Neural Networks-UC Berkeley ...
International Conference on Machine Learning, 2020 2D Digital Image Correlation and Region-Based Convolutional Neural Network in Monitoring and Evaluation of Surface Cracks in Concrete Structural Elements. M. Słoński, M. Tekieli. Materials, 2020 GluonCV and GluonNLP: Deep Learning in Computer Vision...
Machine learning provides high level of assistance to solve real physical problems and to accelerate engineering design process. Several successful examples have been proposed in the literature, demonstrating the power of DL serving as an alternative to the specific physical numerical model. For example...
Spatial accurate mapping of land susceptibility to wind erosion is necessary to mitigate its destructive consequences. In this research, for the first time, we developed a novel methodology based on deep learning (DL) and active learning (AL) models, the