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On the Use of Deep Active Semi-Supervised Learning for Fast Rendering in Global Illumination
Convolution neural networks usually require large labeled data-sets to construct accurate models. However, in many real-world scenarios, such as global illumination, labeling data are a time-consuming and costly human intelligent task. Semi-supervised learning methods leverage this issue by making u...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321082/ https://www.ncbi.nlm.nih.gov/pubmed/34460748 http://dx.doi.org/10.3390/jimaging6090091 |