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A dual-phase deep learning framework for advanced phishing detection using the novel OptSHQCNN approach
Published 2025-07-01“…To improve the effectiveness of the classification approach, the hyperparameters present in the SHQCNN model are fine-tuned using the shuffled shepherd optimization algorithm (SSOA). Results In the post-deployment phase, the URL is encoded using Optimized Bidirectional Encoder Representations from Transformers (OptBERT), after which the features are extracted. …”
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Automated weed and crop recognition and classification model using deep transfer learning with optimization algorithm
Published 2025-08-01“…Artificial intelligence (AI) led image analysis for weed recognition and mainly, machine learning (ML) and deep learning (DL) utilizing images from cultivated lands have commonly been employed in the literature for identifying numerous kinds of weeds that are cultivated beside crops. …”
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Dehazing algorithm for coal mining face dust and fog images based on a semi-supervised network
Published 2025-06-01“…Existing traditional algorithms suffer from poor dehazing effects, over-enhancement, and color distortion. …”
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Petrographic image classification of complex carbonate rocks from the Brazilian pre-salt using convolutional neural networks
Published 2025-08-01“…Abstract Machine learning (ML) algorithms have been widely applied across geosciences for tasks such as data conditioning, resolution enhancement, and image classification. …”
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Facial emotion based smartphone addiction detection and prevention using deep learning and video based learning
Published 2025-05-01“…Based on detected emotions such as happiness, sadness, or anger, the system dynamically shuffles motivational videos using advanced algorithms like Fisher-Yates and Durstenfeld shuffling techniques to promote behavioral change. …”
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Multisensor Diffusion-Driven Optical Image Translation for Large-Scale Applications
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An RTM-Driven Machine Learning Approach for Estimating High-Resolution FAPAR From LANDSAT 5/7/8/9 Surface Reflectance
Published 2025-01-01“…This study developed a practical approach integrating radiative transfer (RT) modeling and machine learning to estimate 30-m FAPAR from Landsat surface reflectance. …”
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Comparison of Transfer Learning Model Performance for Breast Cancer Type Classification in Mammogram Images
Published 2025-02-01“…This work conducted a thorough comparison analysis of eight prevalent pre-trained CNN algorithms (VGG16, ResNet50, AlexNet, MobileNetV2, ShuffleNet, EfficientNet-b0, EfficientNet-b1, and EfficientNet-b2) for breast cancer classification. …”
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A Deep Learning-Driven CAD for Breast Cancer Detection via Thermograms: A Compact Multi-Architecture Feature Strategy
Published 2025-06-01“…Features are primarily obtained from various layers of MobileNet, EfficientNetB0, and ShuffleNet architectures to assess the impact of individual layers on classification performance. …”
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Enhanced Occupational Safety in Agricultural Machinery Factories: Artificial Intelligence-Driven Helmet Detection Using Transfer Learning and Majority Voting
Published 2024-12-01“…The following neural networks were employed: MobileNetV2, ResNet50, DarkNet53, AlexNet, ShuffleNet, DenseNet201, InceptionV3, Inception-ResNetV2, and GoogLeNet. …”
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ST-YOLOv8: Small-Target Ship Detection in SAR Images Targeting Specific Marine Environments
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Predicting Endpoint Temperature of Molten Steel in VD Furnace Refining Process Using Metallurgical Mechanism and Bayesian Optimization XGBoost
Published 2024-11-01“…Then, production data from the steelmaking plant are processed following operational procedures to eliminate missing and abnormal data. …”
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Incorporating Wave-ViT for Breast Cancer Diagnosis Using MRI Imaging
Published 2025-05-01“…Breast MRI, the most sensitive imaging modality for detection, often involves manual review of numerous slices, which is time-intensive and prone to human error. Machine learning (ML) algorithms offer a transformative solution by automating this process, improving efficiency, and enhancing diagnostic accuracy. …”
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