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Found 5 papers, 1 papers with code
STint: Self-supervised Temporal Interpolation for Geospatial Data
Nevertheless, most prevailing temporal interpolation techniques hinge on optical flow, which encodes the motion of pixels between video frames.
Effectiveness of the Recent Advances in Capsule Networks
Convolutional neural networks (CNNs) have revolutionized the field of deep neural networks.
HDRVideo-GAN: Deep Generative HDR Video Reconstruction
We first extract clean LDR frames from noisy LDR video with alternating exposures with a denoising network trained in a self-supervised setting.
Bayesian Deep Learning Hyperparameter Search for Robust Function Mapping to Polynomials with Noise
However, our understanding of how to design Bayesian Deep Learning (BDL) hyperparameters, specifically, the depth, width and ensemble size, for robust function mapping with uncertainty quantification, is still emerging.
Augmented Convolutional LSTMs for Generation of High-Resolution Climate Change Projections
Projection of changes in extreme indices of climate variables such as temperature and precipitation are critical to assess the potential impacts of climate change on human-made and natural systems, including critical infrastructures and ecosystems.
