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Learning to See in the Dark
TLDR
A pipeline for processing low-light images is developed, based on end-to-end training of a fully-convolutional network that operates directly on raw sensor data and replaces much of the traditional image processing pipeline, which tends to perform poorly on such data.
Semantic Image Inpainting with Deep Generative Models
TLDR
A novel method for semantic image inpainting, which generates the missing content by conditioning on the available data, and successfully predicts information in large missing regions and achieves pixel-level photorealism, significantly outperforming the state-of-the-art methods.
Semantic Image Inpainting with Perceptual and Contextual Losses
TLDR
A novel method for image inpainting based on a Deep Convolutional Generative Adversarial Network that can successfully predict semantic information in the missing region and achieve pixel-level photorealism, which is impossible by almost all existing methods.
Seeing Motion in the Dark
TLDR
By carefully designing a learning-based pipeline and introducing a new loss function to encourage temporal stability, a siamese network is trained on static raw videos, for which ground truth is available, such that the network generalizes to videos of dynamic scenes at test time.
Image Restoration with Deep Generative Models
TLDR
This work proposes to design the image prior in a data-driven manner, and learns it using deep generative models, and demonstrates that this learned prior can be applied to many image restoration problems using an unified framework.
NOMA for Energy-Efficient LiFi-Enabled Bidirectional IoT Communication
TLDR
This paper derives closed-form OPA sets based on the identification of the optimal decoding orders in both downlink and uplink channels, which can enable low-complexity power allocation and proposes an adaptive channel and QoS-based user pairing approach by jointly considering users’ channel gains andQoS requirements.
Fuzzy adaptive control particle swarm optimization based on T-S fuzzy model of maglev vehicle suspension system
TLDR
Simulation and experimental results show that the fuzzy adaptive control algorithm optimized by particle swarm optimization can further improve the speed of parameter optimization and the tracking performance of the system in the face of external disturbances and internal system parameter perturbations within a given range of control parameters.
Online phase measuring profilometry for rectilinear moving object by image correction
TLDR
This work proposes an online PMP based on image correction to measure the three-dimensional shape of the rectilinear moving object by reprojected from the oblique view to an aerial view first and then translated based on the feature points of the object.
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