Efficient Image Super-Resolution with Multi-Branch Mixer Transformer by Long Zhang, Yi Wan

“… Deep learning methods have demonstrated significant advancements in single image super-resolution (SISR), with Transformer-based models frequently outperforming CNN-based counterparts in performance. …”
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Wavelet Domain Multidictionary Learning for Single Image Super-Resolution by Xiaomin Wu, Jiulun Fan, Jian Xu, Yanzi Wang

“…Image super-resolution (SR) aims at recovering the high-frequency (HF) details of a high-resolution (HR) image according to the given low-resolution (LR) image and some priors about natural images. …”
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Image Super-Resolution Using Lightweight Multiscale Residual Dense Network by Shilin Li, Ming Zhao, Zhengyun Fang, Yafei Zhang, Hongjie Li

“…The current super-resolution methods cannot fully exploit the global and local information of the original low-resolution image, resulting in loss of some information. …”
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Image Super-Resolution Reconstruction Based on the Lightweight Hybrid Attention Network by Chu Yuezhong, Wang Kang, Zhang Xuefeng, Liu Heng

“…While keeping the receptive field unchanged, a normal convolution and a dilated convolution are used to replace the large kernel convolution. The four times super-resolution experimental results on five data sets, including Set5 and Set14, show that our proposed method performs well in peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). …”
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Super-Resolution and Large Depth of Field Model for Optical Microscope Imaging by Ruo-Peng Zheng, Shu-Bin Liu, Lei Li

“…The method can also be used in other potential applications, such as microscopes, mobile cameras, and telescopes.…”
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Low Carbon Economy Assessment in China Using the Super-SBM Model by Yanhong Ding, Yu Han

“…This review proposes a performance evaluation system of low-carbon economic development based on multiobjective analysis in low-carbon environment. This is a modeling method combining super efficiency and relaxation-based measurement model (super-SBM model), which can effectively measure green innovation efficiency with unexpected outputs and traditional innovation efficiency without unexpected outputs. …”
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Deep Joint Demosaicking and Super-Resolution for Spectral Filter Array Images by Abdelhamid N. Fsian, Jean-Baptiste Thomas, Jon Y. Hardeberg, Pierre Gouton

“…Our experimental results underscore the efficacy of the proposed network, showcasing an improvement of performance both qualitatively and quantitatively when compared to the sequential combination of state-of-the-art demosaicking and super resolution. With our proposed method, we obtained on the ARAD-1K dataset an average PSNR of 48.02 (dB) for domosaicking only, equivalent to the best method of the state-of-the-art. …”
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The Limited Impact of Running Performance on Football Success in the Turkish Super League by Spyridon Plakias, Sotiris Tasoulis, Angelos E. Kyranoudis, Christos Kokkotis, Serafeim Moustakidis

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Attention-assisted dual-branch interactive face super-resolution network by Xujie Wan, Siyu Xu, Guangwei Gao

“…Experimental results demonstrate that ADBINet outperforms existing methods in both quantitative and qualitative facial super-resolution metrics.…”
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Super-resolution microscopy: Shedding new light on blood cell imaging by Huan Deng, Yan Ma, Yu-Hui Zhang

“…The examination of subcellular structures and proteins within blood cells at the nanoscale can provide valuable insights into the health status of an individual, accurate diagnosis, and efficient treatment strategies for diseases. Super-resolution microscopy (SRM) has recently emerged as a cutting-edge tool for the study of blood cells, providing numerous advantages over traditional methods for examining subcellular structures and proteins. …”
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Feature enhanced cascading attention network for lightweight image super-resolution by Feng Huang, Hongwei Liu, Liqiong Chen, Ying Shen, Min Yu

“…The rich and fine-grained high-frequency information are extracted and fused from multiple perceptual layers, thus improving super-resolution (SR) performance. To validate FECAN’s effectiveness, we evaluate it with different complexities by stacking different numbers of high-frequency enhancement modules (HFEM) that contain FECA. …”
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Latent spectral-spatial diffusion model for single hyperspectral super-resolution by Yingsong Cheng, Yong Ma, Fan Fan, Jiayi Ma, Yuan Yao, Xiaoguang Mei

“…In recent years, significant advances have been achieved in addressing super-resolution (SR) tasks for hyperspectral images, primarily through deep learning-based methodologies. …”
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Quantitative evaluation of intensity fidelity of super-resolution reconstruction for structured illumination microscopy by Yujun Tang, Linbo Wang, Gang Wen, Hui Li

“…Super-resolution structured illumination microscopy (SR-SIM) relies heavily on post-processing reconstruction to obtain high-quality SR images from raw data. …”
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PCCN: Polarimetric Contexture Convolutional Network for PolSAR Image Super-Resolution by Lin-Yu Dai, Ming-Dian Li, Si-Wei Chen

“…The proposed method can provide better super-resolution PolSAR images from both polarimetric and spatial viewpoints.…”
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AI-assisted super-resolution cosmological simulations IV: An emulator for deterministic realizations by Xiaowen Zhang, Patrick Lachance, Ankita Dasgupta, Rupert A. C. Croft, Tiziana Di Matteo, Yueying Ni, Simeon Bird, Yin Li

“…Super-resolution (SR) models in cosmological simulations use deep learning (DL) to rapidly enhance low-resolution (LR) runs with statistically correct fine details. …”
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Effects of Outlets on Cracking Risk and Integral Stability of Super-High Arch Dams by Peng Lin, Hongyuan Liu, Qingbin Li, Hang Hu

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Super-Twisting Sliding Mode Control for Gearless PMSG-Based Wind Turbine by Mojtaba Nasiri, Saleh Mobayen, Quan Min Zhu

“…The PMSG is connected to the grid via the back-to-back converter. In the proposed method, the machine side converter regulates the DC-link voltage. …”
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Gradient pooling distillation network for lightweight single image super-resolution reconstruction by Zhiyong Hong, GuanJie Liang, Liping Xiong

“…The single image super-resolution (SISR) is a classical problem in the field of computer vision, aiming to enhance high-resolution details from low-resolution images. …”
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MDRN: Multi-distillation residual network for efficient MR image super-resolution by Liwei Deng, Jingyi Chen, Xin Yang, Sijuan Huang

“…Super-resolution (SR) of magnetic resonance imaging (MRI) is gaining increasing attention for being able to provide detailed anatomical information. …”
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Advances in Light Field Spatial Super-Resolution: A Comprehensive Literature Survey by Wenqi Lyu, Hao Sheng, Wei Ke, Xiao Ma

“…Super-resolution reconstruction of light field images has recently become a central focus in the fields of computational photography and computer vision. …”
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