technology such as machine learning in healthcare has pushed privacy concerns to the point that the handling of sensitive patient data has become paramount. In the context of FL, predictive analytics without data shar...
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Attacks that involve False Data Injection (FDI) provide a substantial risk to the safety and dependability of contemporary power systems. The weaknesses that are present inside the system's infrastructure are expl...
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Multiband transmission (MBT) has appeared as an immediate solution for the network operator to solve the optical fiber capacity crunch problem. However, the quality of the transmission (QoT) in MBT becomes susceptible...
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Ramanujan sums have been shown to have interesting applications in signal processing. Ramanujan subspaces, Ramanujan dictionaries, and Ramanujan filter banks are useful in representing and denoising discrete-time peri...
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Modern wireless systems, especially at millimeter-wave, place increasingly stringent requirements on size, weight, power and cost (SWaP-C). In this talk we present an overview of our recent work on active beamsteering...
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The classification of tomato leaf disease images involves data collection, augmentation, and a training phase using a Convolutional Neural Network (CNN) with nine layers: input, convolutional, pooling, hidden, and out...
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ISBN:
(数字)9798350349788
ISBN:
(纸本)9798350349795
The classification of tomato leaf disease images involves data collection, augmentation, and a training phase using a Convolutional Neural Network (CNN) with nine layers: input, convolutional, pooling, hidden, and output layers. Training utilizes augmented images of 150x150 pixels, with convolutional and pooling layers transforming and reducing image dimensions to extract relevant features for classification by fully connected layers. K-fold cross-validation ensures robustness, with accuracy rates between 83% and 97%. Performance metrics for classes like Bacterial Spot, Early Blight, Healthy, Leaf Mould, and Spider Mites show varying accuracy, recall, and precision, such as Bacterial Spot achieving 83% accuracy, 89% recall, and 91 % precision. The model's effectiveness depends on the quality and quantity of training data, image resolution, and segmentation.
The reconfigurable intelligent surface (RIS) is a promising technology in metamaterial advancements for millimeter wave (mm-Wave) applications that could revolutionize future 6G wireless communications. RIS surfaces o...
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This paper delves into the development and application of an actuator model using MATLAB within virtual test bed settings. The primary objective is to simulate and assess actuator behavior in a controlled digital envi...
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Haptic simulation systems use the sensation of touch to allow users to experience virtual surroundings. In interfaces that are based on impedance, haptics controllers are sampled data that use angular position and vel...
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Coprime arrays are normally used to identify more sources than sensors, using the coarray domain. They can also be used directly in element-space and still have benefits of better accuracy and resolution compared to U...
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