In recent years, the image feature extraction method based on Transformer has become a
research hotspot. However, when using Transformer for image feature extraction, the …

Deep convolutional neural networks (DCNNs) have exhibited excellent feature extraction
and detail reconstruction capabilities for single image super-resolution (SISR) …

In recent years, deep learning super-resolution models for progressive reconstruction have
achieved great success. However, these models which refer to multi-resolution analysis …

Recently, many super-resolution (SR) methods based on convolutional neural networks
(CNNs) have achieved superior performance by utilizing deep and heavy models, which …

Most multimodal medical image fusion (MMIF) methods suffer from insufficient
complementary feature extraction and luminance degradation, such that the fused results …

Recently, Transformer-based models are taken much focus on solving the task of image
super-resolution (SR) due to their ability to achieve better performance. However, these …

Multimodal sentiment analysis (MSA) is important for quickly and accurately understanding
people's attitudes and opinions about an event. However, existing sentiment analysis …

Existing face super-resolution methods depend on deep convolutional networks (DCN) to
recover high-quality reconstructed images. They either acquire information in a single space …

Fruits require different planting techniques at different growth stages. Traditionally, the
maturity stage of fruit is judged visually, which is time-consuming and labor-intensive. Fruits …

Underwater scenes are often affected by issues such as blurred details, color distortion, and
low contrast, which are primarily caused by wavelength-dependent light scattering; these …