Results 11 to 20 of about 55,142 (282)
ISPRS International Journal of Geo-Information, 2023 Explainable Artificial Intelligence (XAI) has the potential to open up black-box machine learning models. XAI can be used to optimize machine learning models, to search for scientific findings, or to improve the understandability of the AI system for the
Cédric Roussel, Klaus Böhm
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A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2021 Recently, artificial intelligence and machine learning in general have demonstrated remarkable performances in many tasks, from image processing to natural language processing, especially with the advent of deep learning. Along with research progress, they have encroached upon many different fields and disciplines.
Erico Tjoa, Cuntai Guan
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Argumentative XAI: A Survey [PDF]
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021 Explainable AI (XAI) has been investigated for decades and, together with AI itself, has witnessed unprecedented growth in recent years. Among various approaches to XAI, argumentative models have been advocated in both the AI and social science literature, as their dialectical nature appears to match some basic desirable features of the explanation ...
Čyras, Kristijonas +4 more
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XAI-KG: Knowledge Graph to Support XAI and Decision-Making in Manufacturing [PDF]
, 2021 The increasing adoption of artificial intelligence requires accurate forecasts and means to understand the reasoning of artificial intelligence models behind such a forecast. Explainable Artificial Intelligence (XAI) aims to provide cues for why a model issued a certain prediction.
Jože M. Rožanec +5 more
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XAI for Predictive Maintenance
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023 The field of Explainable Predictive Maintenance (PM) is concerned with developing methods that can clarify how AI systems operate in the PM domain. One of the challenges of creating maintenance plans is integrating AI output with human decision-making pro- cesses and expertise.
Gama, Joao +5 more
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SeizFt: Interpretable Machine Learning for Seizure Detection Using Wearables
Bioengineering, 2023 This work presents SeizFt—a novel seizure detection framework that utilizes machine learning to automatically detect seizures using wearable SensorDot EEG data.
Irfan Al-Hussaini, Cassie S. Mitchell
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SIGGRAPH Asia 2020 Courses, 2020 • Do Machine Learning algorithms have a Soul? • Could they understand every day's reality as us Humans do? • What the consequence of their Creativity? • Can they help us to understand world better?
Hughes, R +5 more
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Current Directions in Biomedical Engineering, 2022 Deep Learning-based tissue classification may support pathologists in analyzing digitized whole slide images. However, in such critical tasks, only approaches that can be validated by medical experts in advance to deployment, are suitable.
Mohammed Aliya +8 more
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A Model for Classical Space-time Co-ordinates [PDF]
, 1996 Field equations with general covariance are interpreted as equations for a target space describing physical space time co-ordinates, in terms of an underlying base space with conformal invariance.
Bateman H +4 more
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