Establishing an accurate objective evaluation metric of image sharpness is crucial for image
analysis, recognition and quality measurement. In this review, we highlight recent advances …

In recent years, there has been a growing demand for miniaturization, low power
consumption, quick treatments, and non-invasive clinical strategies in the healthcare …

Solar energy is the fastest-growing clean and sustainable energy source, outperforming
other forms of energy generation. Usually, solar panels are low maintenance and do not …

The hybrid architecture of convolutional neural networks (CNNs) and Transformer are very
popular for medical image segmentation. However, it suffers from two challenges. First …

Image segmentation techniques play a vital role in aiding COVID-19 diagnosis. Multi-
threshold image segmentation methods are favored for their computational simplicity and …

Urban feature extraction methods have presented multiple opportunities in the field of
environmental building performance studies, and urban assessments. With reference to …

Automatic crack detection is criticalfor road safety. However, existing models face
challenges due to complicated cracks, difficult backgrounds, and computational inefficiency …

In this paper, a newfangled technique for edge detection that combines the Khalil
conformable derivative and the Hessian matrix is developed and experimentally validated …

This study presents a machine learning-based procedure to automate the charge tuning of
semiconductor spin qubits with minimal human intervention, addressing one of the …

Edge detection in images is a vital application of image processing in fields such as object
detection and identification of lesion regions in medical images. This problem is more …