Machine learning assisted materials design and discovery for rechargeable batteries

Y Liu, B Guo, X Zou, Y Li, S Shi - Energy Storage Materials, 2020‏ - Elsevier
Abstract Machine learning plays an important role in accelerating the discovery and design
process for novel electrochemical energy storage materials. This review aims to provide the …

[PDF][PDF] A review of feature selection and its methods

B Venkatesh, J Anuradha - Cybern. Inf. Technol, 2019‏ - sciendo.com
Nowadays, being in digital era the data generated by various applications are increasing
drastically both row-wise and column wise; this creates a bottleneck for analytics and also …

[كتاب][B] Neural networks and statistical learning

KL Du, MNS Swamy - 2013‏ - books.google.com
Providing a broad but in-depth introduction to neural network and machine learning in a
statistical framework, this book provides a single, comprehensive resource for study and …

Machine learning in energy storage material discovery and performance prediction

G Huang, F Huang, W Dong - Chemical Engineering Journal, 2024‏ - Elsevier
Energy storage material is one of the critical materials in modern life. However, due to the
difficulty of material development, the existing mainstream batteries still use the materials …

Machine learning and radiology

S Wang, RM Summers - Medical image analysis, 2012‏ - Elsevier
In this paper, we give a short introduction to machine learning and survey its applications in
radiology. We focused on six categories of applications in radiology: medical image …

Self-weighted robust LDA for multiclass classification with edge classes

C Yan, X Chang, M Luo, Q Zheng, X Zhang… - ACM Transactions on …, 2020‏ - dl.acm.org
Linear discriminant analysis (LDA) is a popular technique to learn the most discriminative
features for multi-class classification. A vast majority of existing LDA algorithms are prone to …

A survey of face recognition techniques

R Jafri, HR Arabnia - journal of information processing systems, 2009‏ - koreascience.kr
Face recognition presents a challenging problem in the field of image analysis and
computer vision, and as such has received a great deal of attention over the last few years …

A new ranking method for principal components analysis and its application to face image analysis

CE Thomaz, GA Giraldi - Image and vision computing, 2010‏ - Elsevier
In this work, we investigate a new ranking method for principal component analysis (PCA).
Instead of sorting the principal components in decreasing order of the corresponding …

Efficient and robust feature extraction by maximum margin criterion

H Li, T Jiang, K Zhang - Advances in neural information …, 2003‏ - proceedings.neurips.cc
A new feature extraction criterion, maximum margin criterion (MMC), is proposed in this
paper. This new criterion is general in the sense that, when combined with a suitable …

Comparison of texture features based on Gabor filters

SE Grigorescu, N Petkov… - IEEE Transactions on …, 2002‏ - ieeexplore.ieee.org
Texture features that are based on the local power spectrum obtained by a bank of Gabor
filters are compared. The features differ in the type of nonlinear post-processing which is …