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Found 8 papers, 0 papers with code
Investigating Human Factors in Image Forgery Detection
We compare the performance of an automated algorithm and humans for forgery detection problem.
A Structured Approach to Predicting Image Enhancement Parameters
This paper presents a novel approach to predicting the enhancement parameters given a new image using only its features, without using any training images.
Joint Regression and Ranking for Image Enhancement
Research on automated image enhancement has gained momentum in recent years, partially due to the need for easy-to-use tools for enhancing pictures captured by ubiquitous cameras on mobile devices.
Supporting Navigation of Outdoor Shopping Complexes for Visually-impaired Users through Multi-modal Data Fusion
Outdoor shopping complexes (OSC) are extremely difficult for people with visual impairment to navigate.
Classification of Diabetic Retinopathy Images Using Multi-Class Multiple-Instance Learning Based on Color Correlogram Features
All people with diabetes have the risk of developing diabetic retinopathy (DR), a vision-threatening complication.
Improving Vision-based Self-positioning in Intelligent Transportation Systems via Integrated Lane and Vehicle Detection
In the framework, the number of lanes, the vehicle's position in those lanes and the presence of other vehicles are considered as parameters.
A Computational Approach to Relative Aesthetics
To this end, we formulate a novel problem of ranking images with respect to their aesthetic quality.
Relative Learning from Web Images for Content-adaptive Enhancement
Then we carry out subjective tests, which show that users prefer images enhanced by our approach over other existing methods.
