44 citations · 143 across the 17 of their papers we have counts for
4 papers · 1 filter
Provenance Data in the Machine Learning Lifecycle in Computational Science and Engineering
Renan Souza, Leonardo Azevedo, Vítor Lourenço +10
Machine Learning (ML) has become essential in several industries. In Computational Science and Engineering (CSE), the complexity of the ML lifecycle comes from the large variety of…
Semantic Segmentation of Seismic Images
Daniel Civitarese, Daniela Szwarcman, Emilio Vital Brazil +1
Almost all work to understand Earth's subsurface on a large scale relies on the interpretation of seismic surveys by experts who segment the survey (usually a cube) into layers; a…
Netherlands Dataset: A New Public Dataset for Machine Learning in Seismic Interpretation
Reinaldo Mozart Silva, Lais Baroni, Rodrigo S. Ferreira +3
Machine learning and, more specifically, deep learning algorithms have seen remarkable growth in their popularity and usefulness in the last years. This is arguably due to three ma…
Penobscot Dataset: Fostering Machine Learning Development for Seismic Interpretation
Lais Baroni, Reinaldo Mozart Silva, Rodrigo S. Ferreira +3
We have seen in the past years the flourishing of machine and deep learning algorithms in several applications such as image classification and segmentation, object detection and r…