Results 31 to 40 of about 933,026 (316)
Rich Semantics Improve Few-Shot Learning
Proceedings of the British Machine Vision Conference 2021, 2021 Human learning benefits from multi-modal inputs that often appear as rich semantics (e.g., description of an object's attributes while learning about it). This enables us to learn generalizable concepts from very limited visual examples. However, current few-shot learning (FSL) methods use numerical class labels to denote object classes which do not ...
Afham, Mohamed +4 more
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Development of Semantically Rich 3D Retrofit Models [PDF]
Journal of Computing in Civil Engineering, 2020 The use of Building Information Modeling (BIM) has gained considerable interest in new build projects. However, its use in existing assets has been limited to geometric models utilizing point cloud data (PCD) as the primary source of data. The inclusion of nongeometrical data from distributed sources in the geometric model to make it semantically rich ...
Farhad Sadeghineko, Bimal Kumar
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Education Sciences, 2021 Teacher education enables students to grow from ‘novice’ into ‘starting expert’ teachers. In this study, students’ textual peer feedback on video recordings of their teaching practice was analysed to determine the growth of their expertise in relation to
Marije Bent +2 more
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Thangka Image Captioning Based on Semantic Concept Prompt and Multimodal Feature Optimization
Journal of Imaging, 2023 Thangka images exhibit a high level of diversity and richness, and the existing deep learning-based image captioning methods generate poor accuracy and richness of Chinese captions for Thangka images. To address this issue, this paper proposes a Semantic
Wenjin Hu +3 more
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The Cityscapes Dataset for Semantic Urban Scene Understanding [PDF]
Computer Vision and Pattern Recognition, 2016 Visual understanding of complex urban street scenes is an enabling factor for a wide range of applications. Object detection has benefited enormously from large-scale datasets, especially in the context of deep learning.
Marius Cordts +8 more
semanticscholar +1 more source
Towards semantic-rich word embeddings [PDF]
Annals of Computer Science and Information Systems, 2019 In recent years, word embeddings have been shown to improve the performance in NLP tasks such as syntactic parsing or sentiment analysis. While useful, they are problematic in representing ambiguous words with multiple meanings, since they keep a single representation for each word in the vocabulary.
Grzegorz Beringer +4 more
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Structured templates for authoring semantically rich documents [PDF]
Proceedings of the 2007 international workshop on Semantically aware document processing and indexing, 2007 Structured documents associate explicit semantics with content, but authoring rigorously structured documents is a very difficult task. We present a new approach to this issue that adds schema-level information to the popular web formats. This makes editing highly structured documents easier, while ensuring that documents are valid.
Quint, Vincent, Vatton, Irène
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Semantically rich application‐centric security in Android [PDF]
Security and Communication Networks, 2009 ABSTRACTSmartphones are now ubiquitous. However, the security requirements of these relatively new systems and the applications they support are still being understood. As a result, the security infrastructure available in current smartphone operating systems is largely underdeveloped.
Machigar Ongtang +3 more
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bioRxiv, 2018 Language production ultimately aims to convey meaning. Yet, words differ widely in the richness and density of their semantic representations and these differences impact conceptual and lexical processes during speech planning.
Milena Rabovsky, D. Schad, R. A. Rahman
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Towards Semantic Photogrammetry: Generating Semantically Rich Point Clouds from Architectural Close-Range Photogrammetry [PDF]
Sensors, 2022 Developments in the field of artificial intelligence have made great strides in the field of automatic semantic segmentation, both in the 2D (image) and 3D spaces. Within the context of 3D recording technology it has also seen application in several areas, most notably in creating semantically rich point clouds which is usually performed manually.
Arnadi Murtiyoso +4 more
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