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Super-Resolution

Deep Learning in Ultrasound localization Microscopy: Applications and perspectives
Ultrasound Localization Microscopy (ULM) is a novel super-resolution imaging technique that can image the vasculature in vivo at depth …
Pruning Sparse Tensor Neural Networks Enables Deep Learning for 3D Ultrasound Localization Microscopy
Ultrasound Localization Microscopy (ULM) is a non-invasive technique that allows for the imaging of micro-vessels in vivo, at depth and …
Pruning Sparse Tensor Neural Networks Enables Deep Learning for 3D Ultrasound Localization Microscopy
Ultrasound Localization Microscopy (ULM) is a non-invasive technique that allows for the imaging of micro-vessels in vivo, at depth and …
Overnet: Lightweight multi-scale super-resolution with overscaling network
Super-resolution (SR) has achieved great success due to the development of deep convolutional neural networks (CNNs). However, as the …
Hierarchical Residual Attention Network for Single Image Super-Resolution
Convolutional neural networks are the most successful models in single image super-resolution. Deeper networks, residual connections, …
HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite Imagery
Generative deep learning has sparked a new wave of Super-Resolution (SR) algorithms that enhance single images with impressive …