Next-generation deep learning based on simulators and synthetic data
Deep learning (DL) is being successfully applied across multiple domains, yet these models
learn in a most artificial way: they require large quantities of labeled data to grasp even …
learn in a most artificial way: they require large quantities of labeled data to grasp even …
Next-generation deep learning based on simulators and synthetic data.
CM de Melo, A Torralba, L Guibas… - Trends in Cognitive …, 2021 - europepmc.org
Deep learning (DL) is being successfully applied across multiple domains, yet these models
learn in a most artificial way: they require large quantities of labeled data to grasp even …
learn in a most artificial way: they require large quantities of labeled data to grasp even …
[PDF][PDF] Next Generation Deep Learning Based on Simulators and Synthetic Data
CM de Melo, A Torralba, L Guibas, J DiCarlo… - celsodemelo.net
Deep learning is being successfully applied across multiple domains, yet these models
learn in a most artificial way: they require large quantities of labelled data to grasp even …
learn in a most artificial way: they require large quantities of labelled data to grasp even …
Next-generation deep learning based on simulators and synthetic data
CM de Melo, A Torralba, L Guibas, J DiCarlo… - Trends in Cognitive …, 2022 - Elsevier
HighlightsDespite their initial successes, it is becoming apparent that modern deep learning
(DL) models are hindered by an important bottleneck: the need for large quantities of …
(DL) models are hindered by an important bottleneck: the need for large quantities of …
[引用][C] Next-generation deep learning based on simulators and synthetic data
CM de Melo, A Torralba, L Guibas, J DiCarlo… - Trends in Cognitive …, 2022 - cir.nii.ac.jp
Next-generation deep learning based on simulators and synthetic data | CiNii Research
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CiNii 国立情報学研究所 学術情報ナビゲータ[サイニィ] 詳細へ移動 検索フォームへ移動 論文・データを …
[PDF][PDF] Next-generation deep learning based on simulators and synthetic data
CM de Melo, A Torralba, L Guibas, J DiCarlo… - graphics.stanford.edu
Deep learning (DL) is being successfully applied across multiple domains, yet these models
learn in a most artificial way: they require large quantities of labeled data to grasp even …
learn in a most artificial way: they require large quantities of labeled data to grasp even …
Next-generation deep learning based on simulators and synthetic data
CM de Melo, A Torralba, L Guibas… - Trends in cognitive …, 2022 - pubmed.ncbi.nlm.nih.gov
Deep learning (DL) is being successfully applied across multiple domains, yet these models
learn in a most artificial way: they require large quantities of labeled data to grasp even …
learn in a most artificial way: they require large quantities of labeled data to grasp even …
Next-generation deep learning based on simulators and synthetic data
CM de Melo, A Torralba, L Guibas… - Trends in Cognitive …, 2022 - pure.johnshopkins.edu
Deep learning (DL) is being successfully applied across multiple domains, yet these models
learn in a most artificial way: they require large quantities of labeled data to grasp even …
learn in a most artificial way: they require large quantities of labeled data to grasp even …
[PDF][PDF] Next-generation deep learning based on simulators and synthetic data
CM de Melo, A Torralba, L Guibas, J DiCarlo… - graphics.stanford.edu
Deep learning (DL) is being successfully applied across multiple domains, yet these models
learn in a most artificial way: they require large quantities of labeled data to grasp even …
learn in a most artificial way: they require large quantities of labeled data to grasp even …