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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 6 of 6 1 Weak supervision for learning discourse structure in multi-party dialogues ; Supervision distante pour l'apprentissage de structures discursives dans les conversations multi-locuteurs Badene, Sonia. - : HAL CCSD, 2021 In: https://tel.archives-ouvertes.fr/tel-03622653 ; Artificial Intelligence [cs.AI]. Université Paul Sabatier - Toulouse III, 2021. English. ⟨NNT : 2021TOU30138⟩ (2021) BASE Show details 2 Learning a natural-language to LTL executable semantic parser for grounded robotics Wang, Christopher; Ross, Candace; Kuo, Yen-Ling. - : Center for Brains, Minds and Machines (CBMM), Conference on Robot Learning (CoRL), 2020 BASE Show details 3 Weakly-Supervised Crack Detection Dataset ... Inoue, Yuki. - : Zenodo, 2020 Abstract: This repo contains two files: crack detection dataset (weakly_sup_crackdet_dataset.zip), and pretrained TensorFlow model for Xception65 (pascal_voc_seg.zip). The dataset consists of rough annotations used in weakly-supervised crack detection. It contains roughly annotated ground truths for the following datasets: Aigle Crack Forest Dataset DeepCrack Annotations of different "roughness" are stored. Directories suffixed "*_dil*" are synthetically-generated annotations, while directories suffixed "*_rough" and "*_rougher" are manually-generated annotations. The detail of the dataset is described in [1]. Please also refer to our GitHub repo https://github.com/hitachi-rd-cv/weakly-sup-crackdet for more details. This dataset is made available by Hitachi, Ltd. The pretrained model is used by [1]. Please use it for comparison experiments. Please refer to our GitHub repor for more details. [1] Inoue, Y., Nagayoshi, H.: Crack detection as a weakly-supervised problem: Towards achieving less annotation-intensive crack ... Keyword: crack detection; semantic segmentation; weak supervision URL: https://dx.doi.org/10.5281/zenodo.4244083 https://zenodo.org/record/4244083 BASE Hide details 4 Weakly-Supervised Crack Detection Dataset ... Inoue, Yuki. - : Zenodo, 2020 BASE Show details 5 Leveraging large amounts of weakly supervised data for multi-language sentiment classification ... Deriu, Jan; Lucchi, Aurélien; De Luca, Valeria. - : ETH Zurich, 2017 BASE Show details 6 Interactive Learning of Relation Extractors with Weak Supervision Hoffmann, Raphael Dominik. - 2012 BASE Show details

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