In this work, a bibliographic analysis on artificial neural networks (ANNs) using fractional
calculus (FC) theory has been developed to summarize the main features and applications …

Deep neural networks (DNNs) are currently being deployed as machine learning technology
in a wide range of important real-world applications. DNNs consist of a huge number of …

Automated construction of deep neural networks (DNNs) has become a research hot spot
nowadays because DNN's performance is heavily influenced by its architecture and …

Large variations in anatomical shape and size, too much overlap between anatomical
structures, and inconsistent anatomical shapes make accurate lung segmentation in chest x …

Artificial neural network (ANN) is the backbone of machine learning, specifically deep
learning. The interpolating and learning ability of an ANN makes it an ideal tool for …

Prostate segmentation is an important step in prostate volume estimation, multi-modal image
registration, and patient-specific anatomical modeling for surgical planning and image …

Numeral recognition plays a crucial role in creating automated systems such as posting
address sorting and license plate recognition. Nowadays, numeral recognition systems …

The purpose is to make full use of data mining and machine learning technology under big
data to improve the ability of trade financial enterprises to cope with the risk of excessive …

Physical reservoir computing (RC), which can be implemented by various physical systems,
is a low-cost neuromorphic framework with a fast learning capability. In the previous studies …

In this brief, a fractional order proportional-integral-differential neural network (PIDNN)
controller based on the beetle swarm optimization algorithm (BSO-PI D NN) is proposed for …