Feature selection is a dimension reduction technique used to select features that are
relevant to machine learning tasks. Reducing the dataset size by eliminating redundant and …

Simple Summary The goal of this paper is to provide an overview of current radiomic and AI
applications in veterinary diagnostic imaging. We discuss the essential elements of AI for …

Dragonfly Algorithm (DA) is a recent swarm-based optimization method that imitates the
hunting and migration mechanisms of idealized dragonflies. Recently, a binary DA (BDA) …

This paper proposes a binary version of Horse herd Optimization Algorithm (HOA) to tackle
Feature Selection (FS) problems. This algorithm mimics the conduct of a pack of horses …

Texture features within images are actively pursued for accurate and efficient glaucoma
classification. Energy distribution over wavelet subbands is applied to find these important …

The illegal use of electricity, defective meters, and a malfunctioning infrastructure are major
causes of Non-technical losses (NTLs) in electric distribution systems. Although the use of …

This paper proposes new improved binary versions of the Sine Cosine Algorithm (SCA) for
the Feature Selection (FS) problem. FS is an essential machine learning and data mining …

Feature extraction is an important step in Computer Assisted Diagnosis of brain
abnormalities using Magnetic Resonance Images (MRI). Feature Extraction is the process of …

The most vital challenge for a radiologist is locating the brain tumors in the earlier stage. As
the brain tumor grows rapidly, doubling its actual size in about twenty-five days. If not dealt …

The increased utilization of digital instruments like smartphones, Internet of Things (IoT)
sensors, cameras, and microphones has resulted in extensive amounts of big data. Inherent …