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Found 7 papers, 3 papers with code
Human-Centered Evaluation of XAI Methods
In the ever-evolving field of Artificial Intelligence, a critical challenge has been to decipher the decision-making processes within the so-called "black boxes" in deep learning.
A differentiable Gaussian Prototype Layer for explainable Segmentation
We introduce a Gaussian Prototype Layer for gradient-based prototype learning and demonstrate two novel network architectures for explainable segmentation one of which relies on region proposals.
From Attribution Maps to Human-Understandable Explanations through Concept Relevance Propagation
In this work we introduce the Concept Relevance Propagation (CRP) approach, which combines the local and global perspectives and thus allows answering both the "where" and "what" questions for individual predictions.
But that's not why: Inference adjustment by interactive prototype revision
It shows that even correct classifications can rely on unreasonable prototypes that result from confounding variables in a dataset.
Curiously Effective Features for Image Quality Prediction
The performance of visual quality prediction models is commonly assumed to be closely tied to their ability to capture perceptually relevant image aspects.
Deep Neural Networks for No-Reference and Full-Reference Image Quality Assessment
We present a deep neural network-based approach to image quality assessment (IQA).
A Haar Wavelet-Based Perceptual Similarity Index for Image Quality Assessment
In most practical situations, the compression or transmission of images and videos creates distortions that will eventually be perceived by a human observer.
Ranked #12 on
Video Quality Assessment
on MSU FR VQA Database
