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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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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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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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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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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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Granular Syntax Processing with Multi-Task and Curriculum Learning
Syntactic processing techniques are the foundation of natural language processing (NLP), supporting many downstream NLP tasks. In this paper, we...
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Twin Bounded Support Vector Machine with Capped Pinball Loss
In order to obtain a more robust and sparse classifier, in this paper, we propose a novel classifier termed as twin bounded support vector machine...
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Prescribed-Time Sampled-Data Control for the Bipartite Consensus of Linear Multi-Agent Systems in Singed Networks
This article examines the prescribed-time sampled-data control problem for multi-agent systems in signed networks. A time-varying high gain-based...
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TUMDOT–MUC: 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...
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The “Non-Musk” effect at X (Twitter)
Elon Musk, a notable entrepreneur, often influences Wall Street with his controversial social media presence. Drawing on Social Identity and Social...
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Deep learning and embeddings-based approaches for keyphrase extraction: a literature review
Keyphrase extraction is a subtask of natural language processing referring to the automatic extraction of salient terms that semantically capture the...
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Taxonomy of deep learning-based intrusion detection system approaches in fog computing: a systematic review
The Internet of Things (IoT) has been used in various aspects. Fundamental security issues must be addressed to accelerate and develop the Internet...
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Pruning Deep Neural Networks for Green Energy-Efficient Models: A Survey
Over the past few years, larger and deeper neural network models, particularly convolutional neural networks (CNNs), have consistently advanced...
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Exploring AI-driven approaches for unstructured document analysis and future horizons
In the current industrial landscape, a significant number of sectors are grappling with the challenges posed by unstructured data, which incurs...
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Iterative missing value imputation based on feature importance
Many datasets suffer from missing values due to various reasons, which not only increases the processing difficulty of related tasks but also reduces...
