Identifying named entities from PubMed for enriching semantic categories. [PDF]
BMC Bioinformatics, 2015 Controlled vocabularies such as the Unified Medical Language System (UMLS®) and Medical Subject Headings (MeSH®) are widely used for biomedical natural language processing (NLP) tasks.
Kim S, Lu Z, Wilbur WJ.
europepmc +2 more sources
Modeling Noise-Related Timbre Semantic Categories of Orchestral Instrument Sounds With Audio Features, Pitch Register, and Instrument Family [PDF]
Frontiers in Psychology, 2022 Audio features such as inharmonicity, noisiness, and spectral roll-off have been identified as correlates of “noisy” sounds. However, such features are likely involved in the experience of multiple semantic timbre categories of varied meaning and valence.
Lindsey Reymore +3 more
doaj +2 more sources
Semantic Wide and Deep Learning for Detecting Crisis-Information Categories on Social Media [PDF]
International Workshop on the Semantic Web, 2017 When crises hit, many flog to social media to share or consume information related to the event. Social media posts during crises tend to provide valuable reports on affected people, donation offers, help requests, advice provision, etc.
F Atefeh +5 more
core +2 more sources
Reproducibility and discriminability of brain patterns of semantic categories enhanced by congruent audiovisual stimuli. [PDF]
PLoS ONE, 2011 One of the central questions in cognitive neuroscience is the precise neural representation, or brain pattern, associated with a semantic category. In this study, we explored the influence of audiovisual stimuli on the brain patterns of concepts or ...
Yuanqing Li +9 more
doaj +2 more sources
Sex Differences in a Semantic Fluency Task [PDF]
East European Journal of Psycholinguistics, 2015 It is a well-documented empirical fact that men and women perform differently in language tasks involving various semantic categories. The sex-by-category effect has been reported in several languages and through different tasks.
Federico Soriano +6 more
doaj +2 more sources
Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels [PDF]
Computer Vision and Pattern Recognition, 2022 The crux of semi-supervised semantic segmentation is to assign adequate pseudo-labels to the pixels of unlabeled images. A common practice is to select the highly confident predictions as the pseudo ground-truth, but it leads to a problem that most ...
Yuchao Wang +8 more
semanticscholar +1 more source
Unsupervised Semantic Segmentation by Distilling Feature Correspondences [PDF]
International Conference on Learning Representations, 2022 Unsupervised semantic segmentation aims to discover and localize semantically meaningful categories within image corpora without any form of annotation.
Mark Hamilton +4 more
semanticscholar +1 more source
The Lexical Availability of “Daily Activities” in Learners of Spanish (SFL)
Vestnik za Tuje Jezike, 2021 The objective of the present work, which focuses on the teaching and learning of Spanish vocabulary, is to present the lexical availability of Slovene students of Spanish as a foreign language (SFL) in the semantic category “daily activities”.
Marjana Šifrar Kalan
doaj +1 more source
Language-Grounded Indoor 3D Semantic Segmentation in the Wild [PDF]
European Conference on Computer Vision, 2022 Recent advances in 3D semantic segmentation with deep neural networks have shown remarkable success, with rapid performance increase on available datasets.
Dávid Rozenberszki +2 more
semanticscholar +1 more source
Modelling Semantic Categories Using Conceptual Neighborhood [PDF]
Proceedings of the AAAI Conference on Artificial Intelligence, 2020 While many methods for learning vector space embeddings have been proposed in the field of Natural Language Processing, these methods typically do not distinguish between categories and individuals. Intuitively, if individuals are represented as vectors, we can think of categories as (soft) regions in the embedding space.
Schockaert, Steven +3 more
openaire +4 more sources