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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 …
process for novel electrochemical energy storage materials. This review aims to provide the …
[PDF][PDF] A review of feature selection and its methods
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 …
drastically both row-wise and column wise; this creates a bottleneck for analytics and also …
[كتاب][B] Neural networks and statistical learning
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 …
statistical framework, this book provides a single, comprehensive resource for study and …
Machine learning in energy storage material discovery and performance prediction
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 …
difficulty of material development, the existing mainstream batteries still use the materials …
Machine learning and radiology
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 …
radiology. We focused on six categories of applications in radiology: medical image …
Self-weighted robust LDA for multiclass classification with edge classes
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 …
features for multi-class classification. A vast majority of existing LDA algorithms are prone to …
A survey of face recognition techniques
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 …
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
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 …
Instead of sorting the principal components in decreasing order of the corresponding …
Efficient and robust feature extraction by maximum margin criterion
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 …
paper. This new criterion is general in the sense that, when combined with a suitable …
Comparison of texture features based on Gabor filters
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 …
filters are compared. The features differ in the type of nonlinear post-processing which is …