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dcantemel's Projects

adaptive-and-robust-filter-sets

This repository provides the code to train adaptive and robust filter sets using an unsupervised learning framework.

bless

Code for paper - D. Temel and G. AlRegib, “BLeSS: Bio-inspired Low-level Spatiochromatic Similarity Assisted Image Quality Assessment “, the IEEE International Conference on Multimedia and Expo , Seattle, USA, Jul. 11-15, 2016.

boosting-in-iqa

Code for paper - D. Temel and G. AlRegib, "Boosting in image quality assessment," 2016 IEEE 18th International Workshop on Multimedia Signal Processing (MMSP), Montreal, QC, 2016, pp. 1-6.

color-difference-for-iqa

Code for paper - D. Temel and G. AlRegib, "Image quality assessment and color difference," 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Atlanta, GA, 2014, pp. 970-974.

csv

Code for paper - D. Temel and G. AlRegib, “CSV: Image Quality Assessment Based on Color, Structure, and Visual System”, the Signal Processing: Image Communication Journal, vol.48, pp.92-103, October 2016

cure-or

CURE-OR: Challenging Unreal and Real Environments for Object Recognition

cure-tsd

CURE-TSD: Challenging Unreal and Real Environments for Traffic Sign Detection

cure-tsr

CURE-TSR: Challenging Unreal and Real Environments for Traffic Sign Recognition

distorted-representation-characteriziation

Codes for paper "Distorted Representation Space Characterization Through Backpropagated Gradients", ICIP 2019

fault-detection-using-color

Code for paper - Z. Wang, D. Temel and G. AlRegib, "Fault detection using color blending and color transformations," 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Atlanta, GA, 2014, pp. 999-1003.

heartbeat

Code for paper - H. Pan, D. Temel and G. AlRegib, "HeartBEAT: Heart beat estimation through adaptive tracking," 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), Las Vegas, NV, 2016, pp. 587-590.

implicit-background-estimation

Implicit Background Estimation for Semantic Segmentation

ms-unique

This is a demonstration of the algorithm described in the paper "MS-UNIQUE: Multi Model and Sharpness Weighted Unsupervised Image Quality Estimation". Given an original and a distorted image, MS-UNIQUE gives out a score that approximates the perceptual quality of the distorted image.

persim

Code for paper - D. Temel and G. AlRegib, "PerSIM: Multi-resolution image quality assessment in the perceptually uniform color domain," 2015 IEEE International Conference on Image Processing (ICIP), Quebec City, QC, 2015, pp. 1682-1686.

rapd

Healthcare Intelligence: RAPD Assessment

resift

Code for paper - D. Temel and G. AlRegib, "ReSIFT: Reliability-weighted sift-based image quality assessment," 2016 IEEE International Conference on Image Processing (ICIP), Phoenix, AZ, 2016, pp. 2047-2051.

semantic-autoencoder

This repository provides the code to train and classify sparse autoencoder weights based on their semantic meaning.

spatial-pooling-in-iqa

Code for paper - D. Temel and G. AlRegib, "A comparative study of quality and content-based spatial pooling strategies in image quality assessment," 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Orlando, FL, 2015, pp. 732-736.

summer

Code for paper - D. Temel and G. AlRegib, “Perceptual Image Quality Assessment through Spectral Analysis of Error Representations ,” Signal Processing: Image Communication, Volume 70, 2019, Pages 37-46.

unique-unsupervised-image-quality-estimation

This is a demonstration of the algorithm described in the paper "UNIQUE: Unsupervised Image Quality Estimation". Given an original and a distorted image, UNIQUE gives out a score that approximates the perceptual quality of a distorted image.

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