Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
In the last few years, the deep learning (DL) computing paradigm has been deemed the
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …
A comprehensive review on deep learning based remote sensing image super-resolution methods
Satellite imageries are an important geoinformation source for different applications in the
Earth Science field. However, due to the limitation of the optic and sensor technologies and …
Earth Science field. However, due to the limitation of the optic and sensor technologies and …
DeepEMhancer: a deep learning solution for cryo-EM volume post-processing
Cryo-EM maps are valuable sources of information for protein structure modeling. However,
due to the loss of contrast at high frequencies, they generally need to be post-processed to …
due to the loss of contrast at high frequencies, they generally need to be post-processed to …
Scale-mae: A scale-aware masked autoencoder for multiscale geospatial representation learning
Large, pretrained models are commonly finetuned with imagery that is heavily augmented to
mimic different conditions and scales, with the resulting models used for various tasks with …
mimic different conditions and scales, with the resulting models used for various tasks with …
Artificial intelligence in the creative industries: a review
This paper reviews the current state of the art in artificial intelligence (AI) technologies and
applications in the context of the creative industries. A brief background of AI, and …
applications in the context of the creative industries. A brief background of AI, and …
Evaluation and development of deep neural networks for image super-resolution in optical microscopy
Deep neural networks have enabled astonishing transformations from low-resolution (LR) to
super-resolved images. However, whether, and under what imaging conditions, such deep …
super-resolved images. However, whether, and under what imaging conditions, such deep …
Real-world single image super-resolution: A brief review
Single image super-resolution (SISR), which aims to reconstruct a high-resolution (HR)
image from a low-resolution (LR) observation, has been an active research topic in the area …
image from a low-resolution (LR) observation, has been an active research topic in the area …
Fast underwater image enhancement for improved visual perception
In this letter, we present a conditional generative adversarial network-based model for real-
time underwater image enhancement. To supervise the adversarial training, we formulate an …
time underwater image enhancement. To supervise the adversarial training, we formulate an …
Tdan: Temporally-deformable alignment network for video super-resolution
Video super-resolution (VSR) aims to restore a photo-realistic high-resolution (HR) video
frame from both its corresponding low-resolution (LR) frame (reference frame) and multiple …
frame from both its corresponding low-resolution (LR) frame (reference frame) and multiple …
The 2018 PIRM challenge on perceptual image super-resolution
This paper reports on the 2018 PIRM challenge on perceptual super-resolution (SR), held in
conjunction with the Perceptual Image Restoration and Manipulation (PIRM) workshop at …
conjunction with the Perceptual Image Restoration and Manipulation (PIRM) workshop at …