Results 31 to 40 of about 218,873 (322)
GOGGLES: Automatic Image Labeling with Affinity Coding
, 2020 Generating large labeled training data is becoming the biggest bottleneck in building and deploying supervised machine learning models. Recently, the data programming paradigm has been proposed to reduce the human cost in labeling training data. However,
Chaba, Sanya +5 more
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Concept Extraction and Clustering for Topic Digital Library Construction [PDF]
, 2008 This paper is to introduce a new approach to build topic digital library using concept extraction and document clustering. Firstly, documents in a special domain are automatically produced by document classification approach.
Chengzhi, Zhang, Dan, Wu
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Exploring Semi-Automatic Map Labeling [PDF]
Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2019 Extended version of a paper appearing in SIGSPATIAL ...
Fabian Klute +4 more
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IEEE Access, 2020 In this study, we focus on the egocentric segmentation of arms to improve self-perception in Augmented Virtuality (AV). The main contributions of this work are: i) a comprehensive survey of segmentation algorithms for AV; ii) an Egocentric Arm ...
Ester Gonzalez-Sosa +4 more
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Automatic Labeled LiDAR Data Generation based on Precise Human Model
, 2019 Following improvements in deep neural networks, state-of-the-art networks have been proposed for human recognition using point clouds captured by LiDAR. However, the performance of these networks strongly depends on the training data.
Kim, Wonjik +3 more
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FishesThe accurate labeling of species and size of specimens plays a pivotal role in fish auctions conducted at fishing ports. These labels, among other relevant information, serve as determinants of the objectivity of the auction preparation process ...
Javier Jareño +4 more
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Likelihood-based semi-supervised model selection with applications to speech processing
, 2009 In conventional supervised pattern recognition tasks, model selection is typically accomplished by minimizing the classification error rate on a set of so-called development data, subject to ground-truth labeling by human experts or some other means.
Khudanpur, Sanjeev P. +2 more
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Proceedings of International Conferences of Experimental Linguistics, 2019 The paper proposes a framework for automatic prosody labeling. The labeling involves detection of the location of accented syllables and phrase boundaries, and recognition of pitch accent and boundary tone types. A number of classification models are designed to perform these tasks on the basis of small vectors of acoustic features.
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Pedestrian-Crossing Detection Enhanced by CyclicGAN-Based Loop Learning and Automatic Labeling
Applied SciencesPedestrian safety at crosswalks remains a critical concern as traffic accidents frequently result from drivers’ failure to yield, leading to severe injuries or fatalities.
Kuan-Chieh Wang +3 more
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Automatic Annotation of Narrative Radiology Reports
Diagnostics, 2020 Narrative texts in electronic health records can be efficiently utilized for building decision support systems in the clinic, only if they are correctly interpreted automatically in accordance with a specified standard.
Ivan Krsnik +4 more
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