Deep convolutional neural networks (CNNs) have successfully addressed numerous
challenging real-world problems and are known to be more complex and powerful …

With the advancement of wireless communication technology, the number of wireless
network terminals has exploded, and various new business scenarios have emerged. The …

The development of machine learning based models to predict the movement of a financial
market has been a challenging problem due to the low signal-to-noise ratio under the effect …

As a universal approximator, the first order Takagi–Sugeno fuzzy system possesses the
capability to approximate widespread nonlinear systems through a group of IF THEN fuzzy …

Unmanned aerial systems, namely drones, have greatly improved and expanded drastically
over the years. Due to their efficiency and ease of use, drones have been utilized in a wide …

Stochastic configuration networks (SCNs) construct randomized learner models
incrementally in a node-by-node format under the guidance of its supervisory mechanism …

This chapter provides a review of fundamental concepts for interpretable AI in healthcare,
highlighting the currently relevant literature on healthcare analytics, intelligible models, the …

Deep neural network (DNN) has achieved great success in various fields. Due to its high
computing and storage costs, it is difficult to directly deploy them to resource constrained …