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Found 6 papers, 1 papers with code
SeismiQB -- a novel framework for deep learning with seismic data
Unfortunately, many of the seismic processing tools were developed years before the era of machine learning, including the most popular SEG-Y data format for storing seismic cubes.
Seismic horizon detection with neural networks
Over the last few years, Convolutional Neural Networks (CNNs) were successfully adopted in numerous domains to solve various image-related tasks, ranging from simple classification to fine borders annotation.
Benchmarks of ResNet Architecture for Atrial Fibrillation Classification
In this work we apply variations of ResNet architecture to the task of atrial fibrillation classification.
A Simple Probabilistic Model for Uncertainty Estimation
The article focuses on determining the predictive uncertainty of a model on the example of atrial fibrillation detection problem by a single-lead ECG signal.
Clearing noisy annotations for computed tomography imaging
One of the problems on the way to successful implementation of neural networks is the quality of annotation.
Not quite unreasonable effectiveness of machine learning algorithms
State-of-the-art machine learning algorithms demonstrate close to absolute performance in selected challenges.
