Explainable artificial intelligence: a comprehensive review

D Minh, HX Wang, YF Li, TN Nguyen - Artificial Intelligence Review, 2022 - Springer
Thanks to the exponential growth in computing power and vast amounts of data, artificial
intelligence (AI) has witnessed remarkable developments in recent years, enabling it to be …

Automated emotion recognition: Current trends and future perspectives

M Maithri, U Raghavendra, A Gudigar… - Computer methods and …, 2022 - Elsevier
Background Human emotions greatly affect the actions of a person. The automated emotion
recognition has applications in multiple domains such as health care, e-learning …

The state of the art in enhancing trust in machine learning models with the use of visualizations

A Chatzimparmpas, RM Martins, I Jusufi… - Computer Graphics …, 2020 - Wiley Online Library
Abstract Machine learning (ML) models are nowadays used in complex applications in
various domains, such as medicine, bioinformatics, and other sciences. Due to their black …

A visual analytics framework for explaining and diagnosing transfer learning processes

Y Ma, A Fan, J He, AR Nelakurthi… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Many statistical learning models hold an assumption that the training data and the future
unlabeled data are drawn from the same distribution. However, this assumption is difficult to …

A survey of visual analytic pipelines

XM Wang, TY Zhang, YX Ma, J Xia, W Chen - Journal of Computer …, 2016 - Springer
Visual analytics has been widely studied in the past decade. One key to make visual
analytics practical for both research and industrial applications is the appropriate definition …

Recent progress and trends in predictive visual analytics

J Lu, W Chen, Y Ma, J Ke, Z Li, F Zhang… - Frontiers of Computer …, 2017 - Springer
A wide variety of predictive analytics techniques have been developed in statistics, machine
learning and data mining; however, many of these algorithms take a black-box approach in …

Data-driven analysis and prediction of stable phases for high-entropy alloy design

I Peivaste, E Jossou, AA Tiamiyu - Scientific Reports, 2023 - nature.com
High-entropy alloys (HEAs) represent a promising class of materials with exceptional
structural and functional properties. However, their design and optimization pose challenges …

Stock volatility prediction by hybrid neural network

Y Wang, H Liu, Q Guo, S Xie, X Zhang - IEEE Access, 2019 - ieeexplore.ieee.org
Stock price volatility forecasting is a hot topic in time series prediction research, which plays
an important role in reducing investment risk. However, the trend of stock price not only …

Hierarchical support vector machine for facial micro-expression recognition

H Pan, L Xie, Z Lv, J Li, Z Wang - Multimedia Tools and Applications, 2020 - Springer
The sample category distribution of spontaneous facial micro-expression datasets is
unbalanced, due to the experimental environment, collection equipment, and …

Explaining black box models by means of local rules

E Pastor, E Baralis - Proceedings of the 34th ACM/SIGAPP symposium …, 2019 - dl.acm.org
Many high performance machine learning methods produce black box models, which do not
disclose their internal logic yielding the prediction. However, in many application domains …