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Artificial intelligence and machine learning [PDF]
Electronic Markets, 2022 AbstractWithin the last decade, the application of “artificial intelligence” and “machine learning” has become popular across multiple disciplines, especially in information systems. The two terms are still used inconsistently in academia and industry—sometimes as synonyms, sometimes with different meanings.
Niklas Kühl 0001 +3 more
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Implicit Estimation of Paragraph Relevance From Eye Movements
Frontiers in Computer Science, 2022 Eye movements were shown to be an effective source of implicit relevance feedback in constrained search and decision-making tasks. Recent research suggests that gaze-based features, extracted from scanpaths over short news articles (g-REL), can reveal ...
Michael Barz +4 more
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AlphaZe∗∗: AlphaZero-like baselines for imperfect information games are surprisingly strong
Frontiers in Artificial Intelligence, 2023 In recent years, deep neural networks for strategy games have made significant progress. AlphaZero-like frameworks which combine Monte-Carlo tree search with reinforcement learning have been successfully applied to numerous games with perfect information.
Jannis Blüml +5 more
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Artificial Intelligence and Learning Environments: Preface [PDF]
Artificial Intelligence, 1990 This chapter contains sections titled: Rationale for the Collection, Research Standards, Overview of the Articles, Research Trends of the 1980s, New Perspectives ...
Clancey, William J., Soloway, Elliot
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Deep Learning Techniques for Diabetic Retinopathy Classification: A Survey
IEEE Access, 2022 Diabetic Retinopathy (DR) is a degenerative disease that impacts the eyes and is a consequence of Diabetes mellitus, where high blood glucose levels induce lesions on the eye retina.
Mohammad Z. Atwany +2 more
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Meta-learning in natural and artificial intelligence [PDF]
Current Opinion in Behavioral Sciences, 2021 Meta-learning, or learning to learn, has gained renewed interest in recent years within the artificial intelligence community. However, meta-learning is incredibly prevalent within nature, has deep roots in cognitive science and psychology, and is currently studied in various forms within neuroscience. The aim of this review is to recast previous lines
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PUF Modeling Attacks Using Deep Learning and Machine Learning Algorithms
Engineering Proceedings, 2023 The rapid advancement of technology has led to the pervasive presence of electronic devices in our lives, enabling convenience and connectivity. Cryptography offers solutions, but vulnerabilities persist due to physical attacks like malware.
Nelakudite Saadvikaa +4 more
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Application of Machine Learning and Data Mining Techniques in Diagnosing Diabetes [PDF]
Advances in Engineering and Intelligence SystemsDiabetes is a metabolic disorder characterized by high blood glucose levels and is a major health burden worldwide due to serious complications such as cardiovascular disease and chronic renal failure.
Claire Murray +2 more
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Feature Extraction of Ophthalmic Images Using Deep Learning and Machine Learning Algorithms
Engineering Proceedings, 2023 Deep learning and Machine Learning Algorithms has become the most popular method for analyzing and extracting features especially in medical images. And feature extraction has made this task much easier.
Tunuri Sundeep +4 more
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Textual Feature Extraction Using Ant Colony Optimization for Hate Speech Classification
Big Data and Cognitive Computing, 2023 Feature selection and feature extraction have always been of utmost importance owing to their capability to remove redundant and irrelevant features, reduce the vector space size, control the computational time, and improve performance for more accurate ...
Shilpa Gite +6 more
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