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Found 5 papers, 1 papers with code
A semi-supervised methodology for fishing activity detection using the geometry behind the trajectory of multiple vessels
To this end, we leverage the unsupervised nature of cluster analysis to label the trajectory geometry highlighting the changes in the vessel's moving pattern which tends to indicate fishing activity.
SGORNN: Combining Scalar Gates and Orthogonal Constraints in Recurrent Networks
Our experimental results on the addition problem confirm that our combination of orthogonal and scalar gated RNNs are able to outperform both predecessor models on long sequences using only a single RNN cell.
Active learning for medical code assignment
Machine Learning (ML) is widely used to automatically extract meaningful information from Electronic Health Records (EHR) to support operational, clinical, and financial decision-making.
Providing theoretical learning guarantees to Deep Learning Networks
Deep Learning (DL) is one of the most common subjects when Machine Learning and Data Science approaches are considered.
Acoustic Modeling Using a Shallow CNN-HTSVM Architecture
More importantly we isolate the performance of the acoustic model and provide results on both the frame and phoneme level considering the true robustness of the model.
