A review on explainability in multimodal deep neural nets
Artificial Intelligence techniques powered by deep neural nets have achieved much success
in several application domains, most significantly and notably in the Computer Vision …
in several application domains, most significantly and notably in the Computer Vision …
A comprehensive overview of biometric fusion
The performance of a biometric system that relies on a single biometric modality (eg,
fingerprints only) is often stymied by various factors such as poor data quality or limited …
fingerprints only) is often stymied by various factors such as poor data quality or limited …
A new hybrid model for wind speed forecasting combining long short-term memory neural network, decomposition methods and grey wolf optimizer
Reliable and accurate wind speed forecasting (WSF) is fundamental for efficient exploitation
of wind power. In particular, high accuracy short-term WSF (ST-WSF) has a significant …
of wind power. In particular, high accuracy short-term WSF (ST-WSF) has a significant …
[HTML][HTML] A machine learning based credit card fraud detection using the GA algorithm for feature selection
The recent advances of e-commerce and e-payment systems have sparked an increase in
financial fraud cases such as credit card fraud. It is therefore crucial to implement …
financial fraud cases such as credit card fraud. It is therefore crucial to implement …
Investigating the impact of data normalization on classification performance
Data normalization is one of the pre-processing approaches where the data is either scaled
or transformed to make an equal contribution of each feature. The success of machine …
or transformed to make an equal contribution of each feature. The success of machine …
Urban resilience and livability performance of European smart cities: A novel machine learning approach
Smart cities are centres of economic opulence and hope for standardized living.
Understanding the shades of urban resilience and livability in smart city models is of …
Understanding the shades of urban resilience and livability in smart city models is of …
[HTML][HTML] A quantitative discriminant method of elbow point for the optimal number of clusters in clustering algorithm
C Shi, B Wei, S Wei, W Wang, H Liu, J Liu - EURASIP journal on wireless …, 2021 - Springer
Clustering, a traditional machine learning method, plays a significant role in data analysis.
Most clustering algorithms depend on a predetermined exact number of clusters, whereas …
Most clustering algorithms depend on a predetermined exact number of clusters, whereas …
[HTML][HTML] COVID-SCORE: A global survey to assess public perceptions of government responses to COVID-19 (COVID-SCORE-10)
Background Understanding public perceptions of government responses to COVID-19 may
foster improved public cooperation. Trust in government and population risk of exposure …
foster improved public cooperation. Trust in government and population risk of exposure …
Hierarchical fully convolutional network for joint atrophy localization and Alzheimer's disease diagnosis using structural MRI
Structural magnetic resonance imaging (sMRI) has been widely used for computer-aided
diagnosis of neurodegenerative disorders, eg, Alzheimer's disease (AD), due to its …
diagnosis of neurodegenerative disorders, eg, Alzheimer's disease (AD), due to its …
Comparison of Min-Max normalization and Z-Score Normalization in the K-nearest neighbor (kNN) Algorithm to Test the Accuracy of Types of Breast Cancer
The purpose of this study was to examine the results of the prediction of breast cancer,
which have been classified based on two types of breast cancer, malignant and benign. The …
which have been classified based on two types of breast cancer, malignant and benign. The …