Results 51 to 60 of about 10,267 (252)
Average results for SSIM index considering various data rate.
Average results for SSIM index considering various data rate.
Khaled H. Almotairi (13813266)
core +1 more source
To overcome two‐dimensional modulation bottlenecks, Hadamard Matrix Slicing Single‐Pixel Imaging (HMS‐SPI) establishes an efficient one‐dimensional imaging paradigm. By slicing the traditional Hadamard matrix into one‐dimensional encoding vectors and spatially expanding them, the required measurement patterns decrease by a factor of N.
Xiaoxue Li +8 more
wiley +1 more source
GAN-TL: Generative Adversarial Networks with Transfer Learning for MRI Reconstruction
Generative adversarial networks (GAN), which are fueled by deep learning, are an efficient technique for image reconstruction using under-sampled MR data.
Muhammad Yaqub +6 more
doaj +1 more source
Average results for SSIM index considering various vehicle densities.
Average results for SSIM index considering various vehicle densities.
Khaled H. Almotairi (13813266)
core +1 more source
MarginPath is a novel vision‐language system that automates breast cancer margin assessment using a single label‐free multiphoton microscopy image. By integrating tumor‐associated collagen signatures with virtual H&E imaging, it generates accurate margin heatmaps and comprehensive diagnostic reports.
Shu Wang +15 more
wiley +1 more source
INDEX QUALITY ASSESMENT CITRA TERINTERPOLASI (SSIM dan FSIM)
Ada sejumlah aplikasi dalam pengenalan pola yang membutuhkan citra dengan ukuran tertentu. Ukuran citra menentukan hasil dari pengenalan pola suatu sistem. Suatu metode interpolasi digunakan untuk menyesuaikan ukuran suatu citra.
Meirista Wulandari
doaj +1 more source
SSIM-inspired image denoising using sparse representations
Perceptual image quality assessment (IQA) and sparse signal rep-resentation have recently emerged as high-impact research topics in the field of image processing.
Zhou Wang +3 more
core +1 more source
MSE, PSNR, SSIM, RMSE and DSC of 10 images.
MSE, PSNR, SSIM, RMSE and DSC of 10 images.
Sidratul Montaha (13200394) +5 more
core +1 more source
This study introduces a foundation model‐based biomarker for risk stratification of pathological response in non‐small cell lung cancer. A Vision Mamba super‐resolution model standardizes heterogeneous CT images. A multi‐task Swin Transformer then fine‐tunes a pre‐trained lung foundation model to jointly optimize tumor segmentation and response ...
Yanglan Xu +10 more
wiley +1 more source

