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Found 6 papers, 1 papers with code
From Cities to Series: Complex Networks and Deep Learning for Improved Spatial and Temporal Analytics*
Graphs have often been used to answer questions about the interaction between real-world entities by taking advantage of their capacity to represent complex topologies.
DropLeaf: a precision farming smartphone application for measuring pesticide spraying methods
Pesticide application has been heavily used in the cultivation of major crops, contributing to the increase of crop production over the past decades.
Pay Attention to Evolution: Time Series Forecasting with Deep Graph-Evolution Learning
Time-series forecasting is one of the most active research topics in artificial intelligence.
Patient trajectory prediction in the Mimic-III dataset, challenges and pitfalls
Our results demonstrate significant improvements in automated medical prognosis, as measured with Recall@k. We summarize our experience as a set of relevant insights for the design of Deep Learning architectures.
Reconstructing commuters network using machine learning and urban indicators
Here, we propose an alternative approach using machine learning and 22 urban indicators to predict the flow of people and reconstruct the intercity commuters network.
A smartphone application to measure the quality of pest control spraying machines via image analysis
However, their correct use depends on assessment methods that can accurately predict how well the pesticides' spraying covered the intended crop region.
