Results 11 to 20 of about 388,626 (336)
Semi‐supervised classification of fundus images combined with CNN and GCN
Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022 Abstract Purpose Diabetic retinopathy (DR) is one of the most serious complications of diabetes, which is a kind of fundus lesion with specific changes. Early diagnosis of DR can effectively reduce the visual damage caused by DR. Due to the variety and different morphology of DR lesions, automatic classification of fundus images in mass screening can ...
Sixu Duan +8 more
wiley +1 more source
Semantic Relational Object Tracking [PDF]
IEEE Transactions on Cognitive and Developmental Systems, 2020 This paper addresses the topic of semantic world modeling by conjoining probabilistic reasoning and object anchoring. The proposed approach uses a so-called bottom-up object anchoring method that relies on the rich continuous data from perceptual sensor data.
Andreas Persson +3 more
openaire +5 more sources
Vascular endothelial‐cadherin as a marker of endothelial injury in preclinical Alzheimer disease
Annals of Clinical and Translational Neurology, Volume 9, Issue 12, Page 1926-1940, December 2022., 2022 Abstract Objective Endothelial dysfunction is an early and prevalent pathology in Alzheimer disease (AD). We here investigate the value of vascular endothelial‐cadherin (VEC) as a cerebrospinal fluid (CSF) marker of endothelial injury in preclinical AD.
Rawan Tarawneh +5 more
wiley +1 more source
The Semantic Relation of Human and Nature via Mollasadra Transcendental Knowledge (The Role of Nature in Human Inspiration and Perfection) [PDF]
بازیابی دانش و نظامهای معنایی, 2023 IntroductionNature is a theophany of divinity and motion which human lives are considered on it. Human essence along with nature, could lead to a spiritual journey and also help manifest new science to a better green and clean world.
Jana Arabzadeh +4 more
doaj +1 more source
Scene Attribute Semantic Relational Regularization for Transport-Travel Scene Understanding
IEEE Access, 2020 Attribute learning has improved the performance in scene understanding and scene recognition. However, there are many attributes described by words or short texts in a static scene and traffic crowd scene.
Xin Lei Wei +4 more
doaj +1 more source
Instantiation of Relations for Semantic Annotation [PDF]
2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings)(WI'06), 2006 This paper presents a methodology for the semantic annotation of web pages with individuals of a domain ontology. While most semantic annotation systems can recognize knowledge units, they usually do not establish explicit relations between them. The method presented identifies the individuals which should be related among the whole set of individuals ...
Tenier, Sylvain +3 more
openaire +5 more sources
Causal reasoning and symbolic relationships in Medieval Illuminations [PDF]
Journal of Data Mining and Digital Humanities, 2019 This work applies knowledge engineering’s techniques to medieval illuminations. Inside it, an illumination is considered as a knowledge graph which was used by some elites in the Middle Ages to represent themselves as a social group and exhibit the ...
Djibril Diarra +2 more
doaj +1 more source
Co-induction in relational semantics [PDF]
Theoretical Computer Science, 1991 AbstractAn application of the mathematical theory of maximum fixed points of monotonic set operators to relational semantics is presented. It is shown how an important proof method which we call co-induction, a variant of Park's (1969) principle of fixpoint induction, can be used to prove the consistency of the static and the dynamic relational ...
Milner, Robin, Tofte, Mads
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Lexical semantics enhanced neural word embeddings [PDF]
Knowledge-Based Systems, Volume 252,2022, 2022 Current breakthroughs in natural language processing have benefited dramatically from neural language models, through which distributional semantics can leverage neural data representations to facilitate downstream applications. Since neural embeddings use context prediction on word co-occurrences to yield dense vectors, they are inevitably prone to ...
arxiv +1 more source
Learning Turkish Hypernymy Using Word Embeddings
International Journal of Computational Intelligence Systems, 2018 Recently, Neural Network Language Models have been effectively applied to many types of Natural Language Processing (NLP) tasks. One popular type of tasks is the discovery of semantic and syntactic regularities that support the researchers in building a ...
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doaj +1 more source