In the digital multimedia era, digital forensics is becoming an emerging area of research
thanks to the large amount of image and video files generated. Ensuring the integrity of such …

Anomaly-based intrusion detection systems (IDSs) have been deployed to monitor network
activity and to protect systems and the Internet of Things (IoT) devices from attacks (or …

Diabetic Retinopathy (DR) represents a highly-prevalent complication of diabetes in which
individuals suffer from damage to the blood vessels in the retina. The disease manifests …

Diabetes is a very fast‐growing disease in India, with currently more than 72 million patients.
Prolonged diabetes (about almost 20 years) can cause serious loss to the tiny blood vessels …

Featured Application The proposed approach can be applied to any of the Convolutional
Neural Networks-based architecture to explain, evaluate and validate the model's decisions …

Diabetic retinal image classification aims to conduct diabetic retinopathy automatically
diagnosing, which has achieved considerable improvement by deep learning models …

For many manufacturing companies, the production line is very important. In recent years,
the number of small-quantity, high-mix products have been increasing, and the identification …

Recently Inverted Beta-Liouville mixture models have emerged as an efficient paradigm for
proportional positive vectors modeling and unsupervised learning. However, little attention …

The accurate detection of abnormalities in medical images (like X-ray and CT scans) is a
challenging problem due to images' blurred boundary contours, different sizes, variable …

In this paper, we propose a novel hybrid discriminative learning approach based on shifted-
scaled Dirichlet mixture model (SSDMM) and Support Vector Machines (SVMs) to address …