Autoencoder is an unsupervised learning model, which can automatically learn data
features from a large number of samples and can act as a dimensionality reduction method …

Remote sensing is a useful tool for monitoring spatio-temporal variations of crop
morphological and physiological status and supporting practices in precision farming. In …

An autoencoder is a specific type of a neural network, which is mainly designed to encode
the input into a compressed and meaningful representation and then decode it back such …

The construction industry is known to be overwhelmed with resource planning, risk
management and logistic challenges which often result in design defects, project delivery …

Recommender systems provide personalized service support to users by learning their
previous behaviors and predicting their current preferences for particular products. Artificial …

With the wide deployments of heterogeneous networks, huge amounts of data with
characteristics of high volume, high variety, high velocity, and high veracity are generated …

Data assimilation (DA) and uncertainty quantification (UQ) are extensively used in analysing
and reducing error propagation in high-dimensional spatial-temporal dynamics. Typical …

In the Engineering discipline, prognostics play an essential role in improving system safety,
reliability and enabling predictive maintenance decision-making. Due to the adoption of …

Deep learning, which is a subfield of machine learning, has opened a new era for the
development of neural networks. The auto-encoder is a key component of deep structure …

In the era of the Internet of Things (IoT) and Industry 4.0, the indoor usage of smart devices is
expected to increase, thereby making their location information more important. Based on …