Additively manufactured materials and structures: A state-of-the-art review on their mechanical characteristics and energy absorption

Y Wu, J Fang, C Wu, C Li, G Sun, Q Li - International Journal of Mechanical …, 2023‏ - Elsevier
Lightweight materials and structures have been extensively studied for a wide range of
applications in design and manufacturing of more environment-friendly and more …

State of the art in defect detection based on machine vision

Z Ren, F Fang, N Yan, Y Wu - International Journal of Precision …, 2022‏ - Springer
Abstract Machine vision significantly improves the efficiency, quality, and reliability of defect
detection. In visual inspection, excellent optical illumination platforms and suitable image …

Comparative performance analysis of K-nearest neighbour (KNN) algorithm and its different variants for disease prediction

S Uddin, I Haque, H Lu, MA Moni, E Gide - Scientific Reports, 2022‏ - nature.com
Disease risk prediction is a rising challenge in the medical domain. Researchers have
widely used machine learning algorithms to solve this challenge. The k-nearest neighbour …

Interpretable machine learning: Fundamental principles and 10 grand challenges

C Rudin, C Chen, Z Chen, H Huang… - Statistic …, 2022‏ - projecteuclid.org
Interpretability in machine learning (ML) is crucial for high stakes decisions and
troubleshooting. In this work, we provide fundamental principles for interpretable ML, and …

Multi-class confusion matrix reduction method and its application on net promoter score classification problem

I Markoulidakis, G Kopsiaftis, I Rallis… - Proceedings of the 14th …, 2021‏ - dl.acm.org
The paper presents a novel method for reducing a multi-class Confusion Matrix into a 2× 2
version enabling the use of the relevant performance metrics and methods like the Receiver …

On hyperparameter optimization of machine learning algorithms: Theory and practice

L Yang, A Shami - Neurocomputing, 2020‏ - Elsevier
Abstract Machine learning algorithms have been used widely in various applications and
areas. To fit a machine learning model into different problems, its hyper-parameters must be …

A deep look into radiomics

C Scapicchio, M Gabelloni, A Barucci, D Cioni… - La radiologia …, 2021‏ - Springer
Radiomics is a process that allows the extraction and analysis of quantitative data from
medical images. It is an evolving field of research with many potential applications in …

AI models for green communications towards 6G

B Mao, F Tang, Y Kawamoto… - … Surveys & Tutorials, 2021‏ - ieeexplore.ieee.org
Green communications have always been a target for the information industry to alleviate
energy overhead and reduce fossil fuel usage. In the current 5G and future 6G eras, there is …

Machine learning algorithms for social media analysis: A survey

TK Balaji, CSR Annavarapu, A Bablani - Computer Science Review, 2021‏ - Elsevier
Social Media (SM) are the most widespread and rapid data generation applications on the
Internet increase the study of these data. However, the efficient processing of such massive …

State-of-the-art in artificial neural network applications: A survey

OI Abiodun, A Jantan, AE Omolara, KV Dada… - Heliyon, 2018‏ - cell.com
This is a survey of neural network applications in the real-world scenario. It provides a
taxonomy of artificial neural networks (ANNs) and furnish the reader with knowledge of …