LsqGaaaa

LsqGaaaa's Stars

• Po-Hsun-Su/pytorch-ssim

  pytorch structural similarity (SSIM) loss

  Language:Python1.9k368

• WZMIAOMIAO/deep-learning-for-image-processing

  deep learning for image processing including classification and object-detection etc.

  Language:Python23k8k

• Beckschen/TransUNet

  This repository includes the official project of TransUNet, presented in our paper: TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.

  Language:Python2.4k501

• linhandev/dataset

  医学影像数据集列表 『An Index for Medical Imaging Datasets』

  2.6k362

• jeya-maria-jose/Medical-Transformer

  Official Pytorch Code for "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation" - MICCAI 2021

  Language:Python804175

• HuCaoFighting/Swin-Unet

  [ECCVW 2022] The codes for the work "Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation"

  Language:Python1.7k313

• peterhpark/neuroclear

  Neuroclear is a deep-learning-based Python module to train a deep neural network for the task of applying super-resolution to degraded axial resolution in fluorescence microscopy, using a single image stack.

  Language:Jupyter Notebook261

• jiangdat/COMI

  Correction of Out-of-focus Microscopic Images by Deep Learning

  Language:Python52

• aladdinpersson/Machine-Learning-Collection

  A resource for learning about Machine learning & Deep Learning

  Language:Python7.6k2.7k

• aravindiiitb/python-compare-images

  This repository is mainly about comparing two images. The technique used is SSIM. i.e. Structural Similarity Index Measure We use some of the inbuilt functions available in python's skimage library to measure the SSIM value. Along with SSIM we also measure the MSE ( Mean Square Error ) To know more about the SSIM technique Refer Here: https://en.wikipedia.org/wiki/Structural_similarity

  Language:Python3815

• cabooster/UTOM

  Unsupervised content-preserving transformation for optical microscopy

  Language:Python222