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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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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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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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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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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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A multi-source heterogeneous medical data enhancement framework based on lakehouse
Obtaining high-quality data sets from raw data is a key step before data exploration and analysis. Nowadays, in the medical domain, a large amount of...
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Advanced techniques for automated emotion recognition in dogs from video data through deep learning
Inter-species emotional relationships, particularly the symbiotic interaction between humans and dogs, are complex and intriguing. Humans and dogs...
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DeMoS: dense module based gene signature detection through quasi-clique: an application to cervical cancer prognosis
Nowadays, cervical cancer is a leading cause of death among women. Determining the gene signature is one of the major issues in bioinformatics....
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Spatio-temporal wind speed forecasting with approximate Bayesian uncertainty quantification
The prediction of short- and long-term wind speed has great utility for the industry, especially for wind energy generation. Deep neural networks can...
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A novel discrete slash family of distributions with application to epidemiology informatics data
This study puts forward a new class of discrete distribution that can be used by the epidemiologists and medical scientists to model data relating to...
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Temporal analysis of topic modeling output by machine learning techniques
Topic modeling is widely recognized as one of the most effective and significant methods of unsupervised text analysis. This method facilitates...
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Ant Colony Optimization for solving Directed Chinese Postman Problem
The Chinese Postman Problem (CPP) is a well-known optimization problem involving determining the shortest route, modeling the system as an undirected...
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Lyapunov-guided representation of recurrent neural network performance
Recurrent neural networks (RNN) are ubiquitous computing systems for sequences and multivariate time-series data. While several robust RNN...
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Res-MGCA-SE: a lightweight convolutional neural network based on vision transformer for medical image classification
This paper presents a lightweight and accurate convolution neural network (CNN) based on encoder in vision transformer structure, which uses...
