Single‐mask phase contrast and dark‐field imaging methods offer the great advantage of being simple to implement, translating most of the complexity to the numerical side. In this work, we study the impact of the modulation topology on the image quality retrieved both on numerical simulation and experiments.Phase contrast and dark‐field imaging are ...
Clara Magnin +5 more
wiley +1 more source
No Reference Image Quality Assessment based on Multi-Expert Convolutional Neural Networks
No Reference (NR) Image Quality Assessment (IQA) algorithm is capable of measuring the quality of distorted images without referencing the original images. This property is of great importance in image processing, compression, and transmission.
Chunling Fan +3 more
doaj +1 more source
SC-IQA: Shift compensation based image quality assessment for DIBR-synthesized views [PDF]
Depth-image-based-rendering (DIBR) has been used to generate the virtual views for Multi-view videos and Free-viewpoint videos. However, the quality assessment of DIBR-synthesized views is very challenging owing to the new types of distortions induced by inaccurate depth maps, dis-occlusions and image inpainting methods.
Tian, Shishun +3 more
openaire +1 more source
Human tests for machine models: What lies “Beyond the Imitation Game”?
Abstract Benchmarking large language models (LLMs) is a key practice for evaluating their capabilities and risks. This paper considers the development of “BIG Bench,” a crowdsourced benchmark designed to test LLMs “Beyond the Imitation Game.” Drawing on linguistic anthropological and ethnographic analysis of the project's GitHub repository, we examine ...
Noya Kohavi, Anna Weichselbraun
wiley +1 more source
A Distorted-Image Quality Assessment Algorithm Based on a Sparse Structure and Subjective Perception
Most image quality assessment (IQA) algorithms based on sparse representation primarily focus on amplitude information, often overlooking the structural composition of images.
Yang Yang, Chang Liu, Hui Wu, Dingguo Yu
doaj +1 more source
A Visual Saliency-Based Neural Network Architecture for No-Reference Image Quality Assessment
Deep learning has recently been used to study blind image quality assessment (BIQA) in great detail. Yet, the scarcity of high-quality algorithms prevents from developing them further and being used in a real-time scenario.
Jihyoung Ryu
doaj +1 more source
Zoom-IQA: Image Quality Assessment with Reliable Region-Aware Reasoning
Image Quality Assessment (IQA) is a long-standing problem in computer vision. Previous methods typically focus on predicting numerical scores without explanation or providing low-level descriptions lacking precise scores. Recent reasoning-based vision language models (VLMs) have shown strong potential for IQA by jointly generating quality descriptions ...
Liang, Guoqiang +4 more
openaire +2 more sources
Robust and Reversible Thermofluorescence in Solvent‐Free Thermoplastic Polyurethane Composites
Thermofluorescent polymer composites with high‐contrast optical outputs are prepared by solvent‐free blending of indenoquinacridone dye into a thermoplastic polyurethane matrix. The temperature‐dependent fluorescence originates from aggregation–dissociation of the dye molecules, regulated by competing hydrogen bonds from the polymer matrix.
Guanghua Yu +8 more
wiley +1 more source
A method for the evaluation of image quality according to the recognition effectiveness of objects in the optical remote sensing image using machine learning algorithm. [PDF]
Objective and effective image quality assessment (IQA) is directly related to the application of optical remote sensing images (ORSI). In this study, a new IQA method of standardizing the target object recognition rate (ORR) is presented to reflect ...
Tao Yuan +4 more
doaj +1 more source
Socially oriented attention in young children with neurofibromatosis type 1: An eye‐tracking study
Plain language summary: https://onlinelibrary.wiley.com/doi/10.1111/dmcn.70050 Abstract Aim To examine visual engagement to social stimuli and response to joint attention in young children with neurofibromatosis type 1 (NF1) and typically developing peers (controls). Method Forty‐five preschool children were studied cross‐sectionally (mean age [SD] = 4
Kristina M. Haebich +6 more
wiley +1 more source

