CORTEXA
← Browse
crossrefMachine Learning and Knowledge Extraction2023-11-20Cited by 2662

A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS

Juan Terven, Diana-Margarita Córdova-Esparza, Julio-Alejandro Romero-González

YOLO has become a central real-time object detection system for robotics, driverless cars, and video monitoring applications. We present a comprehensive analysis of YOLO’s evolution, examining the innovations and contributions in each iteration from the original YOLO up to YOLOv8, YOLO-NAS, and YOLO with transformers. We start by describing the standard metrics and postprocessing; then, we discuss the major changes in network architecture and training tricks for each model. Finally, we summarize the essential lessons from YOLO’s development and provide a perspective on its future, highlighting potential research directions to enhance real-time object detection systems.

View free PDFSource page

Related papers

crossrefMachine Learning and Knowledge Extraction2026-07-23

From Black Box to Clarity: A Systematic Review of Explainability Methods in Deep Convolutional Neural Networks

Zina Tayari, Mourad Zaied

Deep neural networks (DNNs) have significantly advanced machine perception and reasoning; however, their lack of transparency in decision-making continues to pose a major challenge, particularly in high-stakes domains such as healthcare, finance, and law. This is especially conce…

View free PDFSource page
crossrefMachine Learning and Knowledge Extraction2026-07-22

Rapid Machine Learning–Driven Modeling for Large-Scale Validation and Optimization of Control Variables in Wireless Power Transfer Systems

Oscar García-Izquierdo, José Francisco Sanz, Juan Luis Villa, María Paz Comech, Julio J. Melero

Validating wireless power transfer (WPT) systems for electric vehicles (EVs) is a challenge due to efficiency variations caused by coil misalignments and height differences arising from various vehicle designs. Traditional simulation methods, such as finite element analysis (FEM)…

View free PDFSource page
crossrefMachine Learning and Knowledge Extraction2026-07-22

Alzheimer’s Disease Detection Based on Machine Learning and Deep Learning Frameworks: A Cross-Dataset Comparative Performance Analysis and Assessment of Clinical Readiness

Keenan Ramnarain, Rito Clifford Maswanganyi, Philani Khumalo

Alzheimer’s disease (AD) is the most prevalent neurodegenerative disorder worldwide, affecting approximately 56.9 million people in 2021 and projected to reach 152 million by 2050. Its defining pathological features, amyloid-beta plaques and neurofibrillary tangles, accumulate fo…

View free PDFSource page
crossrefMachine Learning and Knowledge Extraction2026-07-22

Cognitive Friction in Clinical Decision Support: A Comparative Study of Judicial and Adjunct Human–AI Interaction Protocols

Samuele Pe, Laura Bergomi, Giovanna Nicora, Camilla A. Simonelli, Prabhjot Kour, Esperanza Diaz, et al.

Artificial intelligence is increasingly used to support clinical decision making, yet concerns remain regarding algorithmic aversion, automation bias and the preservation of meaningful human oversight; while explainable AI aims to improve transparency, less attention has been dev…

View free PDFSource page
crossrefMachine Learning and Knowledge Extraction2026-07-16

From Assets and Processes to Service Ecosystems: A Hierarchical Digital Twin Framework for Knowledge Representation

Igor Kabashkin

Digital twins (DTs) have become a central paradigm for modeling cyber–physical systems and digital infrastructures, yet the term is applied to very different representations—from physical assets to operational processes and service environments. This ambiguity obscures how the va…

View free PDFSource page
crossrefMachine Learning and Knowledge Extraction2026-07-15

Beyond Forecast Accuracy: Evaluating the Error–Profit Paradox in AI-Based Copper Price Prediction

László Vancsura, Tibor Tatay, Tibor Bareith

Copper is a strategically important commodity whose price dynamics are increasingly affected by structural changes, geopolitical shocks, and the global energy transition. These conditions create substantial challenges for forecasting models and provide a useful setting for evalua…

View free PDFSource page