Algorithms, Volume 18, Issue 10

Artificial intelligence and machine learning have increasingly transformed optometry, enabling automated classification and predictive modeling of eye conditions. In this study, we introduce Optometry Random Forest, an artificial intelligence-based s...

Conventional audio and video codecs are designed for human perception, often discarding subtle spectral cues that are essential for machine-based analysis. To overcome this limitation, we propose a machine-oriented compression framework that reinterp...

This paper provides a detailed breakdown of a minimalist, fundamental Transformer-based architecture for forecasting univariate time series. It describes each processing step in detail, from input embedding and positional encoding to self-attention m...

This paper introduces an effective approach for rotatory fault diagnosis, specifically focusing on centrifugal pumps, by combining complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and feature-level integration. Centrifugal...

Data-driven evolutionary algorithms (DDEAs) are essential computational intelligent methods for solving expensive optimization problems (EOPs). The management of surrogate models for fitness predictions, particularly the selection and integration of...

This paper introduces Contextual Object Grouping (COG), a specific computer vision framework that enables automatic interpretation of technical security diagrams through dynamic legend learning for intelligent sensing applications. Unlike traditional...

This paper presents a novel gateway-centric architecture for context-aware trust evaluation in Internet of Battle Things (IoBT) environments. The system is structured across multiple layers, from embedded sensing devices equipped with internal module...

Transmembrane proteins (TMPs) constitute approximately 30% of the mammalian proteome and are critical targets in biomedical research due to their involvement in signaling, transport, and drug interactions. However, their unique structural characteris...

The rapid expansion of AI applications in various domains demands models that balance predictive power with human interpretability, a requirement that has catalyzed the development of hybrid algorithms combining high accuracy with human-readable outp...

Defect detection in textile manufacturing is critically hampered by the inefficiency of manual inspection and the dual constraints of deep learning (DL) approaches. Specifically, DL models suffer from poor generalization, as the rapid iteration of fa...