Deep learning has recently been used for the analysis of neuroimages, such as structural
magnetic resonance imaging (MRI), functional MRI, and positron emission tomography …

Catastrophic forgetting (CF) refers to the sudden and severe loss of prior information in
learning systems when acquiring new information. CF has been an Achilles heel of standard …

In chemical processes, root cause diagnosis of process faults is highly crucial for efficient
troubleshooting, since if poorly managed, process faults can lead to high-consequence rare …

Machine learning has been increasingly applied in identification of fraudulent transactions.
However, most application systems detect duplicitous activities after they have already …

Colour and texture are two perceptual stimuli that determine, to a great extent, the
appearance of objects, materials and scenes. The ability to process texture and colour is a …

Weed invasions pose a threat to agricultural productivity. Weed recognition and detection
play an important role in controlling weeds. The challenging problem of weed detection is …

The diagnosis of COVID-19 is of vital demand. Several studies have been conducted to
decide whether the chest X-ray and computed tomography (CT) scans of patients indicate …

In situ and real-time monitoring of laser processes are very challenging due to complex
dynamics of the laser-matter interactions. Acoustic emission (AE) technique is often used as …

Root cause analysis of rare but catastrophic events in the chemical process industry must
deal with the challenges of data scarcity that may lead to inaccurate diagnosis. Previously …

Deep-learning-augmented single-pixel imaging (SPI) provides an efficient solution for target
compressive sensing. However, the conventional supervised strategy suffers from laborious …