Academic Articles & Research Papers

Deep Learning for Automatic Vision-Based Recognition of Industrial Surface Defects: A Survey

Automatic vision-based inspection systems have played a key role in product quality assessment for decades through the segmentation, detection, and classification of defects. Historically, machine learning frameworks, based on hand-crafted ...

Evaluating Model Resilience to Data Poisoning Attacks: A Comparative Study

Machine learning (ML) has become a cornerstone of critical applications, but its vulnerability to data poisoning attacks threatens system reliability and trustworthiness. Prior studies have begun to investigate the impact of data poisoning ...

PANDA pediatric arousal neural detection architecture.

Ranking-Based Case Retrieval with Graph Neural Networks in Process-Oriented Case-Based Reasoning

In Process-Oriented Case-Based Reasoning (POCBR), experiential knowledge from previous problem-solving situations is retrieved from a case base to be reused for upcoming problems. The task of retrieval is approached in previous work by usin...

Prediction of bank transaction fraud using TabNet—an adaptive deep learning architecture

The development of online banking has brought about an increase in fraudulent operations, which is a major problem for banks. This study delves into the urgent requirement for interpretable, scalable, and top-notch fraud detection systems b...

Applications of artificial intelligence in intelligent manufacturing: a review

Based on research into the applications of artificial intelligence (AI) technology in the manufacturing industry in recent years, we analyze the rapid development of core technologies in the new era of ‘Internet plus AI’, which is triggerin...

Natural Transports-Inspired Differential Semantic Communications: Intelligent Transceivers Carry Just Differences as Meanings

Communication is a fundamental process in the nature of interconnected entities. Conventional engineering models of information transmission and reception, namely Shannon’s bit communication and Weaver’s semantic communication...

SEMANTIC URBAN MESH SEGMENTATION BASED ON AERIAL OBLIQUE IMAGES AND POINT CLOUDS USING DEEP LEARNING

The use of deep machine learning methods for semantic classification of city mesh models is one of the current trends in geoscience development. Thanks to the thriving development of Convolutional Neural Networks (CNNs) it is now achievable...

A web-based artificial intelligence system for label-free virus classification and detection of cytopathic effects

Abstract Identifying viral replication within cells demands labor-intensive isolation methods, requiring specialized personnel and additional confirmatory tests. To facilitate this process, we developed an AI-powered automated system called...

Cortical Origins of the Flash-Lag Effect Distortions: The Influence of Retinotopic Map Architecture.

QATIPANA: Processes of Individuation on the Relationship Between Art, Machine and Natural Systems

The present research turns around the concepts and processes of Becoming and Individuation where it evidences a functional model based on the articulation of an informational processing system based on the approaches of the philosopher Gilb...

Unmanned Aerial Vehicle for Precision Agriculture: A Review

Digital Precision Agriculture (DPA) is a comprehensive approach to agronomic management that utilizes advanced technologies, such as sensor data analysis and automation, to optimize crop productivity, enhance farm income, and minimize envir...

Big Data for Energy Management and Energy-Efficient Buildings

European buildings are producing a massive amount of data from a wide spectrum of energy-related sources, such as smart meters’ data, sensors and other Internet of things devices, creating new research challenges. In this context, the aim o...

Record‐High Latent Heat, Ultra‐Fast Relaxation and Closed‐Loop Recycling Double‐Brush Polymer Networks for Self‐Adaptive Thermal Interface Management

ABSTRACT In the era of artificial intelligence (AI)‐driven high‐performance computing, phase change materials (PCMs) are critical for high‐flux thermal management. PCMs are evolving toward high enthalpy, low interfacial thermal resistance (...

A physics-informed spatiotemporal graph neural network for photovoltaic power forecasting and micro-anomaly localization

Accurate power forecasting and precise fault diagnosis are critical for the reliable operation of large-scale photovoltaic systems. However, existing data-driven models often fail to capture complex spatiotemporal dependencies and lack phys...

A review of optimization strategies for deep and machine learning in diabetic macular edema

Diabetic macular edema (DME) is a primary contributor to visual impairment in diabetic patients, necessitating precise and prompt analysis for optimal treatment. Recent breakthroughs in deep learning (DL) and machine learning (ML) have yiel...

Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas

We develop a methodology to create data-driven predictive digital twins for optimal risk-aware clinical decision-making. We illustrate the methodology as an enabler for an anticipatory personalized treatment that accounts for uncertainties ...

Leveraging the Potential of Novel Data in Power Line Communication of Electricity Grids

Electricity grids have become an essential part of daily life, even if they are often not noticed in everyday life. We usually only become particularly aware of this dependence by the time the electricity grid is no longer available. Howeve...

<bold>CroSSHeteroFL</bold>: Cross-Stratified Sampling Composition-Fitting to Federated Learning for Heterogeneous Clients

In the large-scale deployment of federated learning (FL) systems, the heterogeneity of clients, such as mobile phones and Internet of Things (IoT) devices with different configurations, constitutes a significant problem regarding fairness, ...

Artificial Intelligence and the Future of Testing

This volume consists of a series of essays written by experts, most of whom participated in a conference conducted by the Educational Testing Service to explore how current fields of artificial intelligence might contribute to ETS's plans t...