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Found 4 papers, 1 papers with code
Testing the Segment Anything Model on radiology data
Deep learning models trained with large amounts of data have become a recent and effective approach to predictive problem solving -- these have become known as "foundation models" as they can be used as fundamental tools for other applications.
Plotting time: On the usage of CNNs for time series classification
We present a novel approach for time series classification where we represent time series data as plot images and feed them to a simple CNN, outperforming several state-of-the-art methods.
A Study of Fitness Landscapes for Neuroevolution
Fitness landscapes are a useful concept to study the dynamics of meta-heuristics.
Ensemble Genetic Programming
Ensemble learning is a powerful paradigm that has been usedin the top state-of-the-art machine learning methods like Random Forestsand XGBoost.
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