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of 14 633
pro vyhledávání: '"Semantic ambiguity"'
Domain adaptation aims to reduce the model degradation on the target domain caused by the domain shift between the source and target domains. Although encouraging performance has been achieved by combining cognitive learning with the self-training pa
Externí odkaz:
http://arxiv.org/abs/2409.18543
Akademický článek
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Publikováno v:
Frontiers in Psychology, Vol 15 (2024)
IntroductionHomonyms are words with multiple, unrelated meanings that share a single form and pronunciation. These words provide valuable insights into how semantic representation is retrieved and selected independently of orthography and phonology.
Externí odkaz:
https://doaj.org/article/570305db513949c98e76306ade4ea648
Growth in computational materials science and initiatives such as the Materials Genome Initiative (MGI) and the European Materials Modelling Council (EMMC) has motivated the development and application of ontologies. A key factor has been increased a
Externí odkaz:
http://arxiv.org/abs/2310.00078
Recently, deep learning-based facial landmark detection has achieved significant improvement. However, the semantic ambiguity problem degrades detection performance. Specifically, the semantic ambiguity causes inconsistent annotation and negatively a
Externí odkaz:
http://arxiv.org/abs/2306.02763
Publikováno v:
In Neural Networks January 2025 181
Autor:
Hao X; School of Artificial Intelligence, Hebei University of Technology, No. 5340, Xiping Road, Tianjin, 300401, China. Electronic address: haoxiaoke@scse.hebut.edu.cn., Liu S; School of Artificial Intelligence, Hebei University of Technology, No. 5340, Xiping Road, Tianjin, 300401, China., Feng C; School of Artificial Intelligence, Hebei University of Technology, No. 5340, Xiping Road, Tianjin, 300401, China., Zhu Y; School of Artificial Intelligence, Hebei University of Technology, No. 5340, Xiping Road, Tianjin, 300401, China.
Publikováno v:
Neural networks : the official journal of the International Neural Network Society [Neural Netw] 2024 Oct 18; Vol. 181, pp. 106806. Date of Electronic Publication: 2024 Oct 18.
Autor:
Southwick, Daniel A., Liu, Zhaoying V., Baldwin, Chayce, Quirk, Abigail L., Ungar, Lyle H., Tsay, Chia-Jung, Duckworth, Angela L.
Publikováno v:
In Organizational Behavior and Human Decision Processes January 2023 174
To generate "accurate" scene graphs, almost all existing methods predict pairwise relationships in a deterministic manner. However, we argue that visual relationships are often semantically ambiguous. Specifically, inspired by linguistic knowledge, w
Externí odkaz:
http://arxiv.org/abs/2103.05271