Papers Explainable artificial intelligence
“Explainable artificial intelligence” 태그가 달린 논문 971편 · 필터 해제
Explainable Artificial Intelligence techniques for interpretation of food datasets: a review
Artificial Intelligence (AI) has become essential for analyzing complex data and solving highly-challenging tasks. It is being applied across numerous disciplines beyond computer science, including Food Engineering, wher…
Decision MakingExplainable artificial intelligenceTowards an Evaluation Framework for Explainable Artificial Intelligence Systems for Health and Well-being
The integration of Artificial Intelligence in the development of computer systems presents a new challenge: make intelligent systems explainable to humans. This is especially vital in the field of health and well-being, …
Explainable artificial intelligenceOn Background Bias of Post-Hoc Concept Embeddings in Computer Vision DNNs
The thriving research field of concept-based explainable artificial intelligence (C-XAI) investigates how human-interpretable semantic concepts embed in the latent spaces of deep neural networks (DNNs). Post-hoc approach…
Explainable artificial intelligenceFocal Cortical Dysplasia Type II Detection Using Cross Modality Transfer Learning and Grad-CAM in 3D-CNNs for MRI Analysis
Focal cortical dysplasia (FCD) type II is a major cause of drug-resistant epilepsy, often curable only by surgery. Despite its clinical importance, the diagnosis of FCD is very difficult in MRI because of subtle abnormal…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)Transfer LearningAm I Being Treated Fairly? A Conceptual Framework for Individuals to Ascertain Fairness
Current fairness metrics and mitigation techniques provide tools for practitioners to asses how non-discriminatory Automatic Decision Making (ADM) systems are. What if I, as an individual facing a decision taken by an AD…
Explainable artificial intelligenceFairnessExplainable AI-Based Interface System for Weather Forecasting Model
Machine learning (ML) is becoming increasingly popular in meteorological decision-making. Although the literature on explainable artificial intelligence (XAI) is growing steadily, user-centered XAI studies have not exten…
Decision MakingExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)Weather ForecastingWhich LIME should I trust? Concepts, Challenges, and Solutions
As neural networks become dominant in essential systems, Explainable Artificial Intelligence (XAI) plays a crucial role in fostering trust and detecting potential misbehavior of opaque models. LIME (Local Interpretable M…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)NavigateSurveyReinforcing Clinical Decision Support through Multi-Agent Systems and Ethical AI Governance
Recent advances in the data-driven medicine approach, which integrates ethically managed and explainable artificial intelligence into clinical decision support systems (CDSS), are critical to ensure reliable and effectiv…
Explainable artificial intelligenceFairnessMortality PredictionPredictionExploring Energy Landscapes for Minimal Counterfactual Explanations: Applications in Cybersecurity and Beyond
Counterfactual explanations have emerged as a prominent method in Explainable Artificial Intelligence (XAI), providing intuitive and actionable insights into Machine Learning model decisions. In contrast to other traditi…
counterfactualExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)FairnessUnraveling Pedestrian Fatality Patterns: A Comparative Study with Explainable AI
Road fatalities pose significant public safety and health challenges worldwide, with pedestrians being particularly vulnerable in vehicle-pedestrian crashes due to disparities in physical and performance characteristics.…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)Logic Explanation of AI Classifiers by Categorical Explaining Functors
The most common methods in explainable artificial intelligence are post-hoc techniques which identify the most relevant features used by pretrained opaque models. Some of the most advanced post hoc methods can generate e…
Explainable artificial intelligenceExplainable AI-Guided Efficient Approximate DNN Generation for Multi-Pod Systolic Arrays
Approximate deep neural networks (AxDNNs) are promising for enhancing energy efficiency in real-world devices. One of the key contributors behind this enhanced energy efficiency in AxDNNs is the use of approximate multip…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)Neural Architecture SearchAutomated Processing of eXplainable Artificial Intelligence Outputs in Deep Learning Models for Fault Diagnostics of Large Infrastructures
Deep Learning (DL) models processing images to recognize the health state of large infrastructure components can exhibit biases and rely on non-causal shortcuts. eXplainable Artificial Intelligence (XAI) can address thes…
Anomaly DetectionExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)Semi-supervised Anomaly Detection+1Explainable AI Components for Narrative Map Extraction
As narrative extraction systems grow in complexity, establishing user trust through interpretable and explainable outputs becomes increasingly critical. This paper presents an evaluation of an Explainable Artificial Inte…
Event DetectionExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)Securing Virtual Reality Experiences: Unveiling and Tackling Cybersickness Attacks with Explainable AI
The synergy between virtual reality (VR) and artificial intelligence (AI), specifically deep learning (DL)-based cybersickness detection models, has ushered in unprecedented advancements in immersive experiences by autom…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)Guarding Digital Privacy: Exploring User Profiling and Security Enhancements
User profiling, the practice of collecting user information for personalized recommendations, has become widespread, driving progress in technology. However, this growth poses a threat to user privacy, as devices often c…
Explainable artificial intelligenceComputational identification of ketone metabolism as a key regulator of sleep stability and circadian dynamics via real-time metabolic profiling
Metabolism plays a crucial role in sleep regulation, yet its effects are challenging to track in real time. This study introduces a machine learning-based framework to analyze sleep patterns and identify how metabolic ch…
Causal InferenceExplainable artificial intelligenceA Data-Driven Exploration of Elevation Cues in HRTFs: An Explainable AI Perspective Across Multiple Datasets
Precise elevation perception in binaural audio remains a challenge, despite extensive research on head-related transfer functions (HRTFs) and spectral cues. While prior studies have advanced our understanding of sound lo…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)GENEOnet: Statistical analysis supporting explainability and trustworthiness
Group Equivariant Non-Expansive Operators (GENEOs) have emerged as mathematical tools for constructing networks for Machine Learning and Artificial Intelligence. Recent findings suggest that such models can be inserted w…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)Robust Intrusion Detection System with Explainable Artificial Intelligence
Machine learning (ML) models serve as powerful tools for threat detection and mitigation; however, they also introduce potential new risks. Adversarial input can exploit these models through standard interfaces, thus cre…
Explainable artificial intelligenceExplainable Artificial Intelligence (XAI)Intrusion Detection