Recycling wastewater of the pul** and paper-making industry are widely considered for
clean production, which heavily rely on the timely and accurate monitoring in paper-making …

Identifying clone code fragments across different languages can enhance the productivity of
software developers in several ways. However, the clone detection task is often studied in …

Fault diagnosis of rotor systems is important to prevent unexpected failures. Recently, deep
learning (DL) methods, such as a convolutional neural network (CNN), have been utilized in …

Despite the growing importance of machine learning in today's organisations, we know
relatively little about how machine learning operates and how it influences calculative …

Sophisticated segmentation of the craniomaxillofacial bones (the mandible and maxilla) in
computed tomography (CT) is essential for diagnosis and treatment planning for …

Background and objective: The cone-beam computed tomography (CBCT) provides three-
dimensional volumetric imaging of a target with low radiation dose and cost compared with …

With the increasing penetration of distributed generators (DGs) and the growing demand for
reliable power sources, it has become imperative to promptly identify anomalies in active …

The prerequisites for groundwater pollution remediation include providing accurate
identification of hydraulic parameters of the contaminated site and retrospecting pollution …

Patients living with neurogenic bladder dysfunction can lose the sensation of their bladder
filling. To avoid over-distension of the urinary bladder and prevent long-term damage to the …

Deep learning methods used for hyperspectral image (HSI) classification often achieve
greater accuracy than traditional algorithms but require large numbers of training epochs. To …