SuperYOLO: Super Resolution Assisted Object Detection in Multimodal Remote Sensing Imagery [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2022 Accurately and timely detecting multiscale small objects that contain tens of pixels from remote sensing images (RSI) remains challenging. Most of the existing solutions primarily design complex deep neural networks to learn strong feature ...
Jiaqi Zhang +5 more
semanticscholar +1 more source
Super sensitivity and super resolution with quantum teleportation [PDF]
, 2018 We propose a method for quantum enhanced phase estimation based on continuous variable (CV) quantum teleportation. The phase shift probed by a coherent state can be enhanced by repeatedly teleporting the state back to interact with the phase shift again ...
Andersen, Ulrik L. +3 more
core +4 more sources
Guided filter-based multi-scale super-resolution reconstruction
CAAI Transactions on Intelligence Technology, 2020 The learning-based super-resolution reconstruction method inputs a low-resolution image into a network, and learns a non-linear mapping relationship between low-resolution and high-resolution through the network.
Xiaomei Feng +3 more
doaj +1 more source
SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Models [PDF]
Neurocomputing, 2021 Single image super-resolution (SISR) aims to reconstruct high-resolution (HR) images from the given low-resolution (LR) ones, which is an ill-posed problem because one LR image corresponds to multiple HR images. Recently, learning-based SISR methods have
Haoying Li +6 more
semanticscholar +1 more source
Super-resolution reconstruction of rock CT images based on Real-ESRGAN
Gong-kuang zidonghua, 2023 Due to factors such as image acquisition equipment and geological environment, rock CT images have low resolution and unclear details. However, existing image super-resolution reconstruction methods are prone to losing details when characterizing high ...
LI Gang +6 more
doaj +1 more source
EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-Resolution [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2023 Recently, convolutional networks have achieved remarkable development in remote sensing image (RSI) super-resolution (SR) by minimizing the regression objectives, e.g., MSE loss.
Yi Xiao +5 more
semanticscholar +1 more source
Role of Atg8 in the regulation of vacuolar membrane invagination
Scientific Reports, 2019 Cellular heat stress can cause damage, and significant changes, to a variety of cellular structures. When exposed to chronically high temperatures, yeast cells invaginate vacuolar membranes.
Ayane Ishii +7 more
doaj +1 more source
Depth Super-Resolution Meets Uncalibrated Photometric Stereo [PDF]
, 2017 A novel depth super-resolution approach for RGB-D sensors is presented. It disambiguates depth super-resolution through high-resolution photometric clues and, symmetrically, it disambiguates uncalibrated photometric stereo through low-resolution depth ...
Cremers, Daniel +3 more
core +2 more sources
A novel disparity-assisted block matching-based approach for super-resolution of light field images [PDF]
, 2018 Currently, available plenoptic imaging technology has limited resolution. That makes it challenging to use this technology in applications, where sharpness is essential, such as film industry.
Farag, Saber, Velisavljević, Vladan
core +2 more sources
Super-Resolution Time of Arrival Estimation Using Random Resampling in Compressed Sensing [PDF]
, 2018 There is a strong demand for super-resolution time of arrival (TOA) estimation techniques for radar applications that can that can exceed the theoretical limits on range resolution set by frequency bandwidth.
Fang SHANG +3 more
core +2 more sources