Search
Search Results
-
Multi-granularity Transformer for Image Super-Resolution
Recently, transformers have made great success in computer vision. Thus far, most of those works focus on high-level tasks, e.g., image...
-
Particle filter based multi-frame image super resolution
In most multi-frame image super-resolution (SR) studies, the process that models the construction of the low-resolution (LR) images from high...
-
Single image super-resolution via deep progressive multi-scale fusion networks
Deep convolutional neural network-based single-image super-resolution (SR) models typically process either upsampled full-resolution or original...
-
Multi-Scale Pixel-Attention Feedback Link Network for Single Image Super-Resolution
AbstractIn recent years, deep learning methods have been widely used in single image super-resolution. However, as the network model increase in...
-
KernelFlexSR: a self-adaptive super-resolution algorithm with multi-path convolution and residual network for dynamic kernel enhancement
Machine learning-based image super-resolution (SR) has garnered increasing research interest in recent years. However, there are two issues that have...
-
Hyperspectral image denoising based on multi-resolution dense memory network
Hyperspectral images (HSIs) denoising is an important pre-processing step since noise will seriously degrade the HSIs quality. In this paper, we...
-
Remote sensing image reconstruction using an asymmetric multi-scale super-resolution network
High-resolution (HR) remote sensing images demonstrate detailed geographical information; however, some remote sensing satellites are incapable of...
-
Attention Based Convolutional Neural Network with Multi-frequency Resolution Feature for Environment Sound Classification
The environmental sound classification has great research significance in the fields of intelligent audio monitoring and other fields. A novel...
-
s-LMPNet: a super-lightweight multi-stage progressive network for image super-resolution
Single image super-resolution (SISR) has achieved great success in recent years due to the representation ability of large and deep models. However,...
-
Detection and classification of skin burns on color images using multi-resolution clustering and the classification of reduced feature subsets
The detection of skin burns on color images and their corresponding classification to identify their intensity degree are useful tools for automatic...
-
IBPNet: a multi-resolution and multi-modal image fusion network via iterative back-projection
Most multi-modal image fusion methods are based on the prerequisite that the source images have the same resolution. However, due to the limitations...
-
Radiological image retrieval technique using multi-resolution texture and shape features
Medical image analysis plays a very indispensable role in providing the best possible medical support to a patient. With the rapid advancements in...
-
MS-RAFT+: High Resolution Multi-Scale RAFT
Hierarchical concepts have proven useful in many classical and learning-based optical flow methods regarding both accuracy and robustness. In this...
-
Total variable-order variation as a regularizer applied on multi-frame image super-resolution
Multi-frame image super-resolution reconstruction focuses on obtaining a high-resolution (HR) image from a low-resolution image. Since the...
-
Graph-Based Representation for Multi-image Super-Resolution
Multi-image super-resolution is a challenging computer vision problem that aims at recovering a high-resolution image from its multiple...
-
A contrastive autoencoder with multi-resolution segment-consistency discrimination for multivariate time series anomaly detection
Most reconstruction-based multivariate time series (MTS) anomaly detection methods tend to learn point-wise information, failing to extract a robust...
-
Accurate Multi-contrast MRI Super-Resolution via a Dual Cross-Attention Transformer Network
Magnetic Resonance Imaging (MRI) is a critical imaging tool in clinical diagnosis, but obtaining high-resolution MRI images can be challenging due to...
-
CCOCSA-based multi-frame sparse coding super-resolution via mutual information-based weighted image fusion
Image super-resolution (SR) is one of the most urgent requirements in many applications in computer vision. Though many techniques have been proposed...
-
Huffman Tree Based Multi-resolution Temporal Convolution Network for Electricity Time Series Prediction
Electricity time series prediction is a fundamental part in electricity system scheduling that maintains the balance between electrical supply and...
-
Multi-branch aware module with channel shuffle pixel-wise attention for lightweight image super-resolution
Deep convolutional neural networks (CNNs) have boosted the performance of image super-resolution (SR) in recent years. However, existing deep...
