Nddepth: Normal-distance assisted monocular depth estimation
Monocular depth estimation has drawn widespread attention from the vision community due
to its broad applications. In this paper, we propose a novel physics (geometry)-driven deep …
to its broad applications. In this paper, we propose a novel physics (geometry)-driven deep …
A super-resolution network for medical imaging via transformation analysis of wavelet multi-resolution
In recent years, deep learning super-resolution models for progressive reconstruction have
achieved great success. However, these models which refer to multi-resolution analysis …
achieved great success. However, these models which refer to multi-resolution analysis …
Model-based deep learning for low-cost IMU dead reckoning of wheeled mobile robot
F Guo, H Yang, X Wu, H Dong, Q Wu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Low-cost inertial measurement units (IMUs) suffer from low sensitivity and high random walk
noise, which makes it challenging to use them directly for dead reckoning. Regular model …
noise, which makes it challenging to use them directly for dead reckoning. Regular model …
Multi-exposure image fusion via perception enhanced structural patch decomposition
Multi-exposure image fusion (MEF) is an affordable and convenient option for high-dynamic-
range imaging. Current MEF methods are prone to visually unrealistic results since they take …
range imaging. Current MEF methods are prone to visually unrealistic results since they take …
Lgabl: Uhd multi-exposure image fusion via local and global aware bilateral learning
Multi-exposure image fusion (MEF) technology is to generate a normally exposed image by
fusing images with different exposure levels. Most of the existing models use CNNs to …
fusing images with different exposure levels. Most of the existing models use CNNs to …
Satellite unsupervised anomaly detection based on deconvolution-reconstructed temporal convolutional autoencoder
H Zhao, M Liu, S Qiu, X Cao - IEEE Transactions on Consumer …, 2023 - ieeexplore.ieee.org
Anomaly detection for orbiting satellites has become a paramount research focus in the
aerospace domain. Data-driven methodologies, employing high-dimensional telemetry data …
aerospace domain. Data-driven methodologies, employing high-dimensional telemetry data …
Efficient knowledge distillation for remote sensing image classification: a CNN-based approach
H Song, C Wei, Z Yong - International Journal of Web Information …, 2023 - emerald.com
Purpose The paper aims to tackle the classification of Remote Sensing Images (RSIs), which
presents a significant challenge for computer algorithms due to the inherent characteristics …
presents a significant challenge for computer algorithms due to the inherent characteristics …
Neural Augmented Exposure Interpolation for HDR Imaging
Brightness order reversal usually appears when two large-exposure-ratio images of a high
dynamic range scene are directly fused together by an existing multi-scale exposure fusion …
dynamic range scene are directly fused together by an existing multi-scale exposure fusion …
Lightweight infrared and visible image fusion technique: Guided gradient optimization driven
Y Song, R Wang, Z Li, S Garg… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Infrared and visible image fusion technology aims to combine data from several spectral
bands in order to increase target identification, processing capabilities, and image quality …
bands in order to increase target identification, processing capabilities, and image quality …
Neural Augmentation Based Saturation Restoration for LDR Images of HDR Scenes
There are shadow and highlight regions in a low-dynamic-range (LDR) image which is
captured from a high-dynamic-range (HDR) scene. It is an ill-posed problem to restore the …
captured from a high-dynamic-range (HDR) scene. It is an ill-posed problem to restore the …