A survey of visual analytics for explainable artificial intelligence methods
G Alicioglu, B Sun - Computers & Graphics, 2022 - Elsevier
Deep learning (DL) models have achieved impressive performance in various domains such
as medicine, finance, and autonomous vehicle systems with advances in computing power …
as medicine, finance, and autonomous vehicle systems with advances in computing power …
The state of the art in enhancing trust in machine learning models with the use of visualizations
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 …
various domains, such as medicine, bioinformatics, and other sciences. Due to their black …
[HTML][HTML] Alfalfa yield prediction using UAV-based hyperspectral imagery and ensemble learning
Alfalfa is a valuable and intensively produced forage crop in the United States, and the
timely estimation of its yield can inform precision management decisions. However …
timely estimation of its yield can inform precision management decisions. However …
[HTML][HTML] Designing a feature selection method based on explainable artificial intelligence
J Zacharias, M von Zahn, J Chen, O Hinz - Electronic Markets, 2022 - Springer
Nowadays, artificial intelligence (AI) systems make predictions in numerous high stakes
domains, including credit-risk assessment and medical diagnostics. Consequently, AI …
domains, including credit-risk assessment and medical diagnostics. Consequently, AI …
[HTML][HTML] UAV-based hyperspectral and ensemble machine learning for predicting yield in winter wheat
Z Li, Z Chen, Q Cheng, F Duan, R Sui, X Huang, H Xu - Agronomy, 2022 - mdpi.com
Winter wheat is a widely-grown cereal crop worldwide. Using growth-stage information to
estimate winter wheat yields in a timely manner is essential for accurate crop management …
estimate winter wheat yields in a timely manner is essential for accurate crop management …
IRVINE: A design study on analyzing correlation patterns of electrical engines
In this design study, we present IRVINE, a Visual Analytics (VA) system, which facilitates the
analysis of acoustic data to detect and understand previously unknown errors in the …
analysis of acoustic data to detect and understand previously unknown errors in the …
[HTML][HTML] Explainable machine learning for knee osteoarthritis diagnosis based on a novel fuzzy feature selection methodology
Abstract Knee Osteoarthritis (ΚΟΑ) is a degenerative joint disease of the knee that results
from the progressive loss of cartilage. Due to KOA's multifactorial nature and the poor …
from the progressive loss of cartilage. Due to KOA's multifactorial nature and the poor …
Visual analytics for machine learning: A data perspective survey
The past decade has witnessed a plethora of works that leverage the power of visualization
(VIS) to interpret machine learning (ML) models. The corresponding research topic, VIS4ML …
(VIS) to interpret machine learning (ML) models. The corresponding research topic, VIS4ML …
[HTML][HTML] Deep learning techniques for hyperspectral image analysis in agriculture: A review
In recent years, there has been a growing emphasis on assessing and ensuring the quality
of horticultural and agricultural produce. Traditional methods involving field measurements …
of horticultural and agricultural produce. Traditional methods involving field measurements …
[HTML][HTML] Leaf area index estimation of pergola-trained vineyards in arid regions based on UAV RGB and multispectral data using machine learning methods
The leaf area index (LAI), a valuable variable for assessing vine vigor, reflects nutrient
concentrations in vineyards and assists in precise management, including fertilization …
concentrations in vineyards and assists in precise management, including fertilization …