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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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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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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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Research performance of higher education institutions in Türkiye: 1980–2022
In recent years, there has been a growing interest in the measurement of research performance. These studies evaluate a country or groups of...
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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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Which older publications are still highly cited in the field of bibliometrics? Contemporary bibliometric citation classics
We find out which older publications (defined here as published before 1991) are nowadays, i.e. during the period [2013–2022], the most cited in...
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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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Journal self-citations trends in sport sciences: an analysis of disciplinary journals from 2013 to 2022
This study reports on the yearly rate of journal self-citation (JSC) in sport sciences, how it changes over time, and its association with journal...
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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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Overcoming alphabetical disadvantage: factors influencing the use of surname initial techniques and their impact on citation rates in the four major disciplines of social sciences
This study investigates the factors influencing surname initial techniques in academic publications and their impact on citation counts. Focusing on...
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Low resource Twi-English parallel corpus for machine translation in multiple domains (Twi-2-ENG)
Although Ghana does not have one unique language for its citizens, the Twi dialect stands a chance of fulfilling this purpose. Twi is among the...
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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...
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VAE-GNA: a variational autoencoder with Gaussian neurons in the latent space and attention mechanisms
Variational autoencoders (VAEs) are generative models known for learning compact and continuous latent representations of data. While they have...
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DQN-PACG: load regulation method based on DQN and multivariate prediction model
Demand response plays a pivotal role in modern smart grid systems, aiding in balancing energy consumption. However, the increasing energy demands of...
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Scalable Bayesian p-generalized probit and logistic regression
The logit and probit link functions are arguably the two most common choices for binary regression models. Many studies have extended the choice of...
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LightCapsGNN: light capsule graph neural network for graph classification
Graph neural networks (GNNs) have achieved excellent performances in many graph-related tasks. However, they need appropriate pooling operations to...
