Search alternatives:
based optimization » whale optimization (Expand Search)
based detection » case detection (Expand Search), rapid detection (Expand Search), cancer detection (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
binary case » binary mask (Expand Search), binary image (Expand Search), primary case (Expand Search)
data based » data used (Expand Search)
case based » made based (Expand Search), game based (Expand Search), rate based (Expand Search)
based optimization » whale optimization (Expand Search)
based detection » case detection (Expand Search), rapid detection (Expand Search), cancer detection (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
binary case » binary mask (Expand Search), binary image (Expand Search), primary case (Expand Search)
data based » data used (Expand Search)
case based » made based (Expand Search), game based (Expand Search), rate based (Expand Search)
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MSE for ILSTM algorithm in binary classification.
Published 2023“…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …”
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Joint Detection of Change Points in Multichannel Single-Molecule Measurements
Published 2021“…We validate the algorithm on simulated data and characterize the power of detection and false positive rate. …”
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Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things
Published 2025“…In general, BRBPNN does not show any optimization adaption methods to determine the optimal parameter for appropriate detection. Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …”
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Confusion metrics using LR-HaPi algorithm.
Published 2024“…Nonetheless, the purview of propaganda detection transcends textual data alone. Deep learning algorithms like Artificial Neural Networks (ANN) offer the capability to manage multimodal data, incorporating text, images, audio, and video, thereby considering not only the content itself but also its presentation and contextual nuances during dissemination.…”
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Confusion metrics using MNB-HaPi algorithm.
Published 2024“…Nonetheless, the purview of propaganda detection transcends textual data alone. Deep learning algorithms like Artificial Neural Networks (ANN) offer the capability to manage multimodal data, incorporating text, images, audio, and video, thereby considering not only the content itself but also its presentation and contextual nuances during dissemination.…”
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Confusion metrics using DT-HaPi algorithm.
Published 2024“…Nonetheless, the purview of propaganda detection transcends textual data alone. Deep learning algorithms like Artificial Neural Networks (ANN) offer the capability to manage multimodal data, incorporating text, images, audio, and video, thereby considering not only the content itself but also its presentation and contextual nuances during dissemination.…”
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Confusion metrics using SVM-HaPi algorithm.
Published 2024“…Nonetheless, the purview of propaganda detection transcends textual data alone. Deep learning algorithms like Artificial Neural Networks (ANN) offer the capability to manage multimodal data, incorporating text, images, audio, and video, thereby considering not only the content itself but also its presentation and contextual nuances during dissemination.…”
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LITNET-2020 data splitting approach.
Published 2023“…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …”
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Algoritmo de detección de odio en español (Algorithm for detection of hate speech in Spanish)
Published 2024“…</p><p dir="ltr">Más información:</p><ul><li><a href="https://www.hatemedia.es/" rel="nofollow" target="_blank">https://www.hatemedia.es/</a> o contactar con: <a href="mailto:elias.said@unir.net" target="_blank">elias.said@unir.net</a></li><li>Este algoritmo está relacionado con el algoritmo de clasificación de expresiones de odio por intensidad en español, desarrollado también por los autores: <a href="https://github.com/esaidh266/Algorithm-for-classifying-hate-expressions-by-intensities-in-Spanish" target="_blank">https://github.com/esaidh266/Algorithm-for-classifying-hate-expressions-by-intensities-in-Spanish</a></li><li>Este algoritmo está relacionado con el algoritmo de clasificación de expresiones de odio por tipo en español, desarrollado también por los autores: <a href="https://github.com/esaidh266/Algorithm-for-classifying-hate-expressions-by-type-in-Spanish" target="_blank">https://github.com/esaidh266/Algorithm-for-classifying-hate-expressions-by-type-in-Spanish</a></li></ul><p>----</p>Hate Speech Detection Model<p dir="ltr">This code implements a hate speech classification system using the RoBERTuito model (a Spanish version of RoBERTa) to detect hate speech in tweets.…”
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Data_Sheet_1_Automatic Detection for Multi-Labeled Cardiac Arrhythmia Based on Frame Blocking Preprocessing and Residual Networks.PDF
Published 2021“…<p>Introduction: Electrocardiograms (ECG) provide information about the electrical activity of the heart, which is useful for diagnosing abnormal cardiac functions such as arrhythmias. Recently, several algorithms based on advanced structures of neural networks have been proposed for auto-detecting cardiac arrhythmias, but their performance still needs to be further improved. …”
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