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The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…It was demonstrated from the simulation investigation that the CWT model could yield a better signal transformation amongst the preprocessing algorithms. In addition, amongst the eighteen TL models evaluated based on the CWT transformation, fourteen was f ound to be able to extract the features reasonable, i.e., VGG16, VGG19, ResNet101, ResNet101 V2, ResNet152, ResNet152 V2, Inception V3, Inception ResNet V2, Xception, MobileNetV2, DenseNet 121, DenseNet 169, NasNetMobile and NasNetLarge. …”
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The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach
Published 2001“…Using the developed algorithm, the safety measures involved are such as reliability index and the probability of failure; instead of only factor of safety if conventional deterministic approach is used. …”
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Feature Extraction on Medical Image using 2D Gabor Filter
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Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…The third proposed segmentation algorithm involves two pipelines for feature extraction: split & merge methods and Contextual Encoding Network (EncNet) with an attention mechanism. …”
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Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine
Published 2023“…Also, a corridor extraction algorithm has been developed to extract the region of interest (ROI) around the transmission towers. …”
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Application of Fuzzy C-Means with YCbCr and DenseNet-201 for Automated Corn Leaf Disease Detection
Published 2021“…This is due to instability and complexity of the network. Hence, algorithm that performed better is required. Thus, in this study, image segmentation method of Fuzzy C-Means with YCbCr and image classification method of DenseNet-201 to detect plant leaf diseases is proposed. …”
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Multi-method diagnosis of CT images for rapid detection of intracranial hemorrhages based on deep and hybrid learning
Published 2022“…The first system is proposed by three pretrained deep learning models, which are GoogLeNet, ResNet-50 and AlexNet. The second proposed system using a hybrid technology consists of two parts: the first part is the GoogLeNet, ResNet-50 and AlexNet models for extracting feature maps, while the second part is the SVM algorithm for classifying feature maps. …”
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The Classification of Wink-Based EEG Signals: The identification on efficiency of transfer learning models by means of kNN classifier
Published 2021“…It was shown through this study, that the features extracted by means of NasNetLarge were more efficient compared with NasNetMobile. …”
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Semantic focus fusion based on deep learning for deblurring effect
Published 2024“…In a rapid development of intelligent computation, such as deep learning algorithm, multi-focus image fusion methods indirectly being involved, such as CNN and PCA Net architectures. …”
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Leveraging CQT-VMD and pre-trained AlexNet architecture for accurate pulmonary disease classification from lung sound signals
Published 2025“…This study presents a novel algorithm for classifying pulmonary diseases using lung sound signals by integrating Variational Mode Decomposition (VMD) and the Constant-Q Transform (CQT) within a pre-trained AlexNet convolutional neural network. …”
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Classification and detection of intelligent house resident activities using multiagent
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A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal
Published 2019“…The method employs the intelligence of deep CNN (DenseNet Model) to extract the features after training the model on a wide range of food categories and images. …”
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Supervised ANN classification for engineering machined textures based on enhanced features extraction and reduction scheme
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Food tour recommendation using modified ant colony algorithm
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