DBCNN
Image quality assessor
A deep learning-based system for assessing the quality of images without their original references.
Blind Image Quality Assessment Using A Deep Bilinear Convolutional Neural Network
108 stars
4 watching
21 forks
Language: MATLAB
last commit: over 3 years ago
Linked from 1 awesome list
bilinear-poolingbiqadeep-learningimage-quality-assessmentiqamatconvnetmatlab
uhub/awesome-matlabRelated projects:
| Repository | Description | Stars |
|---|---|---|
 ocampor/image-quality | Library providing a set of tools and algorithms for evaluating the quality of digital images | 401 |
 dsoellinger/blind_image_quality_toolbox | A collection of algorithms and tools for assessing the quality of images without comparing them to a reference image | 158 |
 yunxiaoshi/neural-image-assessment | Trains neural networks to assess image aesthetics using pre-trained models and custom datasets | 538 |
 bestivictory/ilgnet | A deep learning-based framework for image aesthetics assessment using a convolutional neural network structure | 112 |
 cleanlab/cleanvision | Automatically detects issues in image datasets to improve computer vision models | 1,034 |
 zcyang/imageqa-san | This project provides code for training image question answering models using stacked attention networks and convolutional neural networks. | 108 |
 lonl/cdbn | An implementation of Convolutional Deep Belief Networks with support for different computation methods and CUDA acceleration | 35 |
 truskovskiyk/nima.pytorch | Assesses and evaluates images using deep learning models | 335 |
 luzzu/framework | An integrated platform for assessing Linked Data quality using a library of generic and user-provided metrics | 10 |
 zhengpeng7/birefnet | This project provides an implementation of a deep learning model for image segmentation tasks, including background removal and object detection. | 1,417 |
 cszn/dpsr | A deep learning-based method to improve image quality by reducing blur effects | 837 |
| cszn/bsrgan | A deep learning-based approach to super-resolution of degraded images. | 1,217 |
| cszn/ircnn | This project trains deep CNN denoisers to improve image restoration tasks such as deblurring and demosaicking through model-based optimization methods. | 602 |
 abe404/root_painter | An open-source tool for training deep learning models for image analysis | 59 |
 aman-chauhan/image-coloring | Develops a neural network to color grayscale images using local and global features | 2 |