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Data reduction in big data: a survey of methods, challenges and future directions
Data reduction plays a pivotal role in managing and analyzing big data, which is characterized by its volume, velocity, variety, veracity, value,...
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A Meta-learner approach to multistep-ahead time series prediction
The utilization of machine learning has become ubiquitous in addressing contemporary challenges in data science. Moreover, there has been significant...
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Dynamic event-triggered adaptive control for state-constrained strict-feedback nonlinear systems with guaranteed feasibility conditions
In this paper, a new dynamic event-triggered control solution is presented for state-constrained strict-feedback nonlinear systems. The current...
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Decoding the black box: LIME-assisted understanding of Convolutional Neural Network (CNN) in classification of social media tweets
The rise of social media has brought both opportunities and challenges to the digital age, including the proliferation of online trolls that have...
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Extract Implicit Semantic Friends and Their Influences from Bipartite Network for Social Recommendation
Social recommendation often incorporates trusted social links with user-item interactions to enhance rating prediction. Although methods that...
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KHACDD: a knowledge-based hybrid method for multilabel sentiment analysis on complex sentences using attentive capsule and dual structured recurrent network
Using a machine to mine public opinion saves money and time. Traditional sentiment analysis approaches are typically unable to handle multi-meaning...
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Negative-sample-free knowledge graph embedding
Recently, knowledge graphs (KGs) have been shown to benefit many machine learning applications in multiple domains (e.g. self-driving, agriculture,...
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A robust hubness-based algorithm for image data stream classification
Image data stream classification is in high demand and can be used in various contexts, such as public security, medicine, and remote sensing....
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Principal components-based quantification of hierarchical k-core assortativity
Hierarchical networks typically get rated to be not assortative on the basis of the degrees of the end vertices of the edges. However, degree...
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Video anomaly localization using modified faster RCNN with soft NMS algorithm
Localization of anomalies in surveillance videos is a critical component of smart and intelligent surveillance systems. The goal of anomaly detection...
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An efficient facial emotion recognition using convolutional neural network with local sorting binary pattern and whale optimization algorithm
Facial emotion recognition is one of the fields of machine learning and pattern recognition. Facial expression recognition is used in a variety of...
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Similarity-based face image retrieval using sparsely embedded deep features and binary code learning
Human face retrieval has long been established as one of the most interesting research topics in computer vision. With the recent development of deep...
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TUMDOTâMUC: Data Collection and Processing of Multimodal Trajectories Collected by Aerial Drones
Currently available trajectory data sets undoubtedly provide valuable insights into traffic events, the behavior of road users and traffic flow...
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Storage of weights and retrieval method (SWARM) approach for neural networks hybridized with conformal prediction to construct the prediction intervals for energy system applications
The prediction intervals represent the uncertainty associated with the model-predicted responses that impacts the sequential decision-making...
