Nowadays, everyone requires a good quality software. The quality of software can't be
assured due to lack of data availability for training, and testing. Thus, Transfer Learning (TL) …

Infrared and visible image fusion (IVIF) aims to obtain an image that contains
complementary information about the source images. However, it is challenging to define …

In chemical industries, many important tasks such as process design and monitoring rely on
the availability of a good model. A high-performance data-driven prediction model is desired …

The fault diagnosis of power transformers is a challenging problem. The massive
multisource fault is heterogeneous, the type of fault is undetermined sometimes, and one …

Telemonitoring is the use of electronic devices such as smartphones to remotely monitor
patients. It provides great convenience and enables timely medical decisions. To facilitate …

Coordination abilities are required for artificial agents with a high level of autonomy (also
called autonomy agents) to perform collaborative work with humans in human-autonomy …

In partial label learning (PLL) problem, each training sample corresponds to a group of
candidate labels, in which only one label is the ground-truth label (correct label). Almost all …

Transfer Learning (TL) is a design methodology within machine learning (ML) that aims to
utilise knowledge gained while solving one problem to solve a different but related problem …

Machine learning is a rapidly developing technology that enables a system to automatically
learn and improve from experience. Modern machine learning algorithms have achieved …

Software analysis is of vital importance in the assessment of software characteristics. It is
usually based on software measurement and techniques derived from both statistics and …