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Neural Computing and Applications
Scopus
ISSN 0941-0643 · Springer Science+Business Media · 19 artikel di indeks
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Artikel Jurnal Teks lengkap
Data Augmentation techniques in time series domain: a survey and taxonomy
Abstract With the latest advances in deep learning-based generative models, it has not taken long to take advantage of their remarkable performance in the area of time series. Deep neural networks used to work with time series heavily depend on the size and consistency of the datasets used in…
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An improved fire detection approach based on YOLO-v8 for smart cities
Abstract Fires in smart cities can have devastating consequences, causing damage to property, and endangering the lives of citizens. Traditional fire detection methods have limitations in terms of accuracy and speed, making it challenging to detect fires in real time. This paper proposes an…
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A modified Adam algorithm for deep neural network optimization
Abstract Deep Neural Networks (DNNs) are widely regarded as the most effective learning tool for dealing with large datasets, and they have been successfully used in thousands of applications in a variety of fields. Based on these large datasets, they are trained to learn the relationships between…
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Deep learning techniques to classify agricultural crops through UAV imagery: a review
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Human emotion recognition from EEG-based brain–computer interface using machine learning: a comprehensive review
Abstract Affective computing, a subcategory of artificial intelligence, detects, processes, interprets, and mimics human emotions. Thanks to the continued advancement of portable non-invasive human sensor technologies, like brain–computer interfaces (BCI), emotion recognition has piqued the…
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Attention mechanism in neural networks: where it comes and where it goes
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Pima Indians diabetes mellitus classification based on machine learning (ML) algorithms
This paper proposes an e-diagnosis system based on machine learning (ML) algorithms to be implemented on the Internet of Medical Things (IoMT) environment, particularly for diagnosing diabetes mellitus (type 2 diabetes). However, the ML applications tend to be mistrusted because of their inability…
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Deep neural network correlation learning mechanism for CT brain tumor detection
Abstract Modern medical clinics support medical examinations with computer systems which use Computational Intelligence on the way to detect potential health problems in more efficient way. One of the most important applications is evaluation of CT brain scans, where the most precise results come…
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Parallel spatio-temporal attention-based TCN for multivariate time series prediction
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A review of artificial intelligence applied to path planning in UAV swarms
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An efficient optimization approach for designing machine learning models based on genetic algorithm
Abstract Machine learning (ML) methods have shown powerful performance in different application. Nonetheless, designing ML models remains a challenge and requires further research as most procedures adopt a trial and error strategy. In this study, we present a methodology to optimize the…
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A transformer-based approach to irony and sarcasm detection
Abstract Figurative language (FL) seems ubiquitous in all social media discussion forums and chats, posing extra challenges to sentiment analysis endeavors. Identification of FL schemas in short texts remains largely an unresolved issue in the broader field of natural language processing, mainly…
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Evolutionary algorithms and their applications to engineering problems
Abstract The main focus of this paper is on the family of evolutionary algorithms and their real-life applications. We present the following algorithms: genetic algorithms, genetic programming, differential evolution, evolution strategies, and evolutionary programming. Each technique is presented…
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Arabic handwriting recognition system using convolutional neural network
Abstract Automatic handwriting recognition is an important component for many applications in various fields. It is a challenging problem that has received a lot of attention in the past three decades. Research has focused on the recognition of Latin languages’ handwriting. Fewer studies have been…