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Overview
- satellite data
- multispectral
- convolutional neural networks
- invariant representations
- air pollution
Publications
Predicting Multivariate Air Pollution: A Gaussian-Mixture Nested Factorial Variational Autoencoder Approach.
IEEE Geosci. Remote. Sens. Lett.
CombineDeepNet: A Deep Network for Multistep Prediction of Near-Surface PM$_{2.5}$ Concentration.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens.
Towards A Framework for Privacy-Preserving Pedestrian Analysis.
WACV
Actor-Centric Spatio-Temporal Feature Extraction for Action Recognition.
CVIP (1)
BiLSTM-BiGRU: A Fusion Deep Neural Network For Predicting Air Pollutant Concentration.
IGARSS
Self-Supervised Learning for Invariant Representations from Multi-Spectral and SAR Images.
CoRR