Search Results for author:
Found 4 papers, 0 papers with code
Deep Learning for Multi-Label Learning: A Comprehensive Survey
Multi-label learning is a rapidly growing research area that aims to predict multiple labels from a single input data point.
Kalman Filter Based Multiple Person Head Tracking
For multi-target tracking, target representation plays a crucial rule in performance.
Multi-Modal Machine Learning for Flood Detection in News, Social Media and Satellite Sequences
In this paper we present our methods for the MediaEval 2019 Mul-timedia Satellite Task, which is aiming to extract complementaryinformation associated with adverse events from Social Media andsatellites.
A deep learning approach for analyzing the composition of chemometric data
We trained L2 regularized sparse autoencoder end-to-end for reducing the size of the feature vector to handle the classic problem of the curse of dimensionality in chemometric data analysis.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
