An appropriate image segmentation algorithm is required for discriminating between full
grains and grain impurities. In this study, a lightweight fully convolutional segmentation …

Imbalanced datasets pose pervasive challenges in numerous machine learning (ML)
applications, notably in areas such as fraud detection, where fraudulent cases are vastly …

Massive jellyfish outbreaks have put human lives and marine ecosystems in great danger.
As a result, the jellyfish detection methods have drawn a lot of attention, following two …

Pulse repetition interval modulation (PRIM) is integral to radar identification in modern
electronic support measure (ESM) and electronic intelligence (ELINT) systems. Various …

This manuscript presents a new benchmark for assessing the quality of visual summaries
without the need for human annotators. It is based on the Signature Transform, specifically …

This study presents a novel methodology for classifying automotive parts by implementing
the Transfer Learning technique, utilizing the InceptionV3 architecture. We use a proprietary …

A unique method for improving the intelligent agents in retinal image processing is the
proposed RAUGAN (Residual Attention UNet GAN) model. Reliability, accuracy, and …

Object recognition in images is one of the problems that continues to be faced in the world of
computer vision. Various approaches have been developed to address this problem, and …

In this paper, we examine the efficacy of unsupervised learning approaches, particularly
clustering and dimensionality reduction techniques, in practical applications such as image …

The rapid integration of Artificial Intelligence (AI) has significantly improved healthcare
outcomes, especially in ophthalmology. However, Deep learning algorithms are often called …