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Found 6 papers, 1 papers with code
Abductive reasoning as the basis to reproduce expert criteria in ECG Atrial Fibrillation identification
Objective: This work aims at providing a new method for the automatic detection of atrial fibrillation, other arrhythmia and noise on short single lead ECG signals, emphasizing the importance of the interpretability of the classification results.
Let's Dance: Learning From Online Dance Videos
We present a comparison of numerous state-of-the-art techniques on our dataset using three different representations (video, optical flow and multi-person pose data) in order to analyze these approaches.
Arrhythmia Classification from the Abductive Interpretation of Short Single-Lead ECG Records
In this work we propose a new method for the rhythm classification of short single-lead ECG records, using a set of high-level and clinically meaningful features provided by the abductive interpretation of the records.
Discovering Picturesque Highlights from Egocentric Vacation Videos
We present an approach for identifying picturesque highlights from large amounts of egocentric video data.
Predicting Daily Activities From Egocentric Images Using Deep Learning
We collected a dataset of 40, 103 egocentric images over a 6 month period with 19 activity classes and demonstrate the benefit of state-of-the-art deep learning techniques for learning and predicting daily activities.
A method for context-based adaptive QRS clustering in real-time
The method processes the QRS complexes sequentially, grouping them into a dynamic set of clusters based on the information content of the temporal context.
