Results 11 to 20 of about 12,744 (261)
OVERVIEW OF COMPUTER VISION SUPERVISED LEARNING TECHNIQUES FOR LOW-DATA TRAINING [PDF]
Journal of Engineering Science (Chişinău), 2020 In the age of big data and machine learning the costs to turn the data into fuel for the algorithms is prohibitively high. Organizations that can train better models with fewer annotation efforts will have a competitive edge.
BURLACU, Alexandru
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Safe Weakly Supervised Learning [PDF]
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021 Weakly supervised learning (WSL) refers to learning from a large amount of weak supervision data. This includes i) incomplete supervision (e.g., semi-supervised learning); ii) inexact supervision (e.g., multi-instance learning) and iii) inaccurate supervision (e.g., label noise learning). Unlike supervised learning which typically achieves performance
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MetaFL: Metamorphic fault localisation using weakly supervised deep learning
IET Software, 2023 Deep‐Learning‐based Fault Localisation (DLFL) leverages deep neural networks to learn the relationship between statement behaviour and program failures, showing promising results.
Lingfeng Fu +5 more
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International Journal of Applied Earth Observations and Geoinformation, 2022 Semantic segmentation of large-scale mobile laser scanning (MLS) point clouds is essential for urban scene understanding. However, most of the existing semantic segmentation methods require a large quantity of labeled data, which are labor-intensive and ...
Xiangda Lei +7 more
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Weakly Supervised Causal Representation Learning
Advances in Neural Information Processing Systems 35, 2022 Learning high-level causal representations together with a causal model from unstructured low-level data such as pixels is impossible from observational data alone. We prove under mild assumptions that this representation is however identifiable in a weakly supervised setting. This involves a dataset with paired samples before and after random, unknown
Johann Brehmer +3 more
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Agriculture, 2020 Rice is one of the most important staple food sources worldwide. Effective and cheap monitoring of rice planting areas is demanded by many developing countries.
Mo Wang, Jing Wang, Li Chen
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Weakly supervised learning of allomorphy [PDF]
Proceedings of the First Workshop on Subword and Character Level Models in NLP, 2017 Most NLP resources that offer annotations at the word segment level provide morphological annotation that includes features indicating tense, aspect, modality, gender, case, and other inflectional information. Such information is rarely aligned to the relevant parts of the words—i.e. the allomorphs, as such annotation would be very costly.
Miikka Silfverberg, Mans Hulden
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Weakly-Supervised Learning of Human Dynamics [PDF]
, 2020 This paper proposes a weakly-supervised learning framework for dynamics estimation from human motion. Although there are many solutions to capture pure human motion readily available, their data is not sufficient to analyze quality and efficiency of movements.
Petrissa Zell +2 more
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Learning Weakly-Supervised Contrastive Representations
CoRR, 2022 We argue that a form of the valuable information provided by the auxiliary information is its implied data clustering information. For instance, considering hashtags as auxiliary information, we can hypothesize that an Instagram image will be semantically more similar with the same hashtags. With this intuition, we present a two-stage weakly-supervised
Yao-Hung Hubert Tsai +5 more
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Weakly-Supervised Learning of Visual Relations [PDF]
2017 IEEE International Conference on Computer Vision (ICCV), 2017 This paper introduces a novel approach for modeling visual relations between pairs of objects. We call relation a triplet of the form (subject, predicate, object) where the predicate is typically a preposition (eg. 'under', 'in front of') or a verb ('hold', 'ride') that links a pair of objects (subject, object).
Julia Peyre +3 more
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