Search alternatives:
selection algorithm » detection algorithm (Expand Search), detection algorithms (Expand Search)
image learning » maze learning (Expand Search), face learning (Expand Search), aware learning (Expand Search)
selection algorithm » detection algorithm (Expand Search), detection algorithms (Expand Search)
image learning » maze learning (Expand Search), face learning (Expand Search), aware learning (Expand Search)
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Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm
Published 2025“…In this work, we propose a novel framework that integrates </p><p dir="ltr">Convolutional Neural Networks (CNNs) for image classification and a binary Grey Wolf Optimization (GWO) </p><p dir="ltr">algorithm for feature selection. …”
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ROC curve for binary classification.
Published 2024“…To achieve this, we focused the study on addressing the challenge of image noise, which impacts the performance of deep learning models. …”
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Confusion matrix for binary classification.
Published 2024“…To achieve this, we focused the study on addressing the challenge of image noise, which impacts the performance of deep learning models. …”
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A* Path-Finding Algorithm to Determine Cell Connections
Published 2025“…The integration of heuristic optimization and machine learning significantly enhances both speed and precision in astrocyte data analysis. …”
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Data_Sheet_1_Pneumonia detection by binary classification: classical, quantum, and hybrid approaches for support vector machine (SVM).pdf
Published 2024“…Our aim is to develop a machine learning tool that can accurately classify images as belonging to normal or infected individuals. …”
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Supplementary file 1_Comparative evaluation of fast-learning classification algorithms for urban forest tree species identification using EO-1 hyperion hyperspectral imagery.docx
Published 2025“…</p>Discussion<p>The results highlight that integrating dimensionality reduction and optimal band selection with ensemble learning substantially improves classification efficiency and accuracy. …”
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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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