Results 1 to 10 of about 2,605,876 (309)
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
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
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
Decoding of semantic categories of imagined concepts of animals and tools in fNIRS
Journal of Neural Engineering, 2021 Objective. Semantic decoding refers to the identification of semantic concepts from recordings of an individual’s brain activity. It has been previously reported in functional magnetic resonance imaging and electroencephalography.
M. Rybář, R. Poli, I. Daly
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
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
Brain Sciences, 2023 The concreteness effect (CE), namely a better performance with concrete compared to abstract concepts, is a constant feature in healthy people, and it usually increases in persons with aphasia (PWA).
Martina Mancano, Costanza Papagno
doaj +1 more source
Frontiers in Psychology, 2022 With the assistance of the corpus analysis tool Wmatrix 4.0, this paper analyzes the semantic categories of the top 10 commercial banks of China and the United States to figure out their social-cultural behavior in the Internet business context.
Heng Fu, Huifen Zhu
doaj +1 more source
SED: A Simple Encoder-Decoder for Open-Vocabulary Semantic Segmentation [PDF]
Computer Vision and Pattern Recognition, 2023 Open-vocabulary semantic segmentation strives to distinguish pixels into different semantic groups from an open set of categories. Most existing methods explore utilizing pre-trained vision-language models, in which the key is to adapt the image-level ...
Bin Xie +4 more
semanticscholar +1 more source