Explainable artificial intelligence: an analytical review

PP Angelov, EA Soares, R Jiang… - … : Data Mining and …, 2021 - Wiley Online Library
This paper provides a brief analytical review of the current state‐of‐the‐art in relation to the
explainability of artificial intelligence in the context of recent advances in machine learning …

A survey on deep learning and its applications

S Dong, P Wang, K Abbas - Computer Science Review, 2021 - Elsevier
Deep learning, a branch of machine learning, is a frontier for artificial intelligence, aiming to
be closer to its primary goal—artificial intelligence. This paper mainly adopts the summary …

Graph neural networks: foundation, frontiers and applications

L Wu, P Cui, J Pei, L Zhao, X Guo - … of the 28th ACM SIGKDD Conference …, 2022 - dl.acm.org
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …

The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix …

D Chicco, N Tötsch, G Jurman - BioData mining, 2021 - Springer
Evaluating binary classifications is a pivotal task in statistics and machine learning, because
it can influence decisions in multiple areas, including for example prognosis or therapies of …

A comprehensive survey on deep graph representation learning

W Ju, Z Fang, Y Gu, Z Liu, Q Long, Z Qiao, Y Qin… - Neural Networks, 2024 - Elsevier
Graph representation learning aims to effectively encode high-dimensional sparse graph-
structured data into low-dimensional dense vectors, which is a fundamental task that has …

Machine learning in aerodynamic shape optimization

J Li, X Du, JRRA Martins - Progress in Aerospace Sciences, 2022 - Elsevier
Abstract Machine learning (ML) has been increasingly used to aid aerodynamic shape
optimization (ASO), thanks to the availability of aerodynamic data and continued …

Recent advances on image edge detection: A comprehensive review

J Jing, S Liu, G Wang, W Zhang, C Sun - Neurocomputing, 2022 - Elsevier
Edge detection is one of the most important and fundamental problems in the field of
computer vision and image processing. Edge contours extracted from images are widely …

The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation

D Chicco, G Jurman - BMC genomics, 2020 - Springer
Background To evaluate binary classifications and their confusion matrices, scientific
researchers can employ several statistical rates, accordingly to the goal of the experiment …

[HTML][HTML] Supervised machine learning models for prediction of COVID-19 infection using epidemiology dataset

LJ Muhammad, EA Algehyne, SS Usman, A Ahmad… - SN computer …, 2021 - Springer
Abstract COVID-19 or 2019-nCoV is no longer pandemic but rather endemic, with more than
651,247 people around world having lost their lives after contracting the disease. Currently …

[HTML][HTML] A compilation of UAV applications for precision agriculture

P Radoglou-Grammatikis, P Sarigiannidis, T Lagkas… - Computer Networks, 2020 - Elsevier
Climate change has introduced significant challenges that can affect multiple sectors,
including the agricultural one. In particular, according to the Food and Agriculture …