Traditional models like KNN and SVM were not immune either. Their non-differentiable structures made them incompatible with gradient-based attacks like FGSM or PGD, but they remained susceptible to ...

This layer, which included support vector regression (SVR), artificial neural networks (ANN), and AdaBoost, estimated their link to corrosion failure. Electrochemical impedance spectroscopy (EIS) data ...

Scene classification is a dominant track in computer vision tasks as it can help in many missions such as navigation, preprocessing, big data organization, albuming systems, and recognition ...

Graph Neural Networks (GNNs) exhibit satisfactory performance on homophilic networks, where most edges connect two nodes with the same label. However, their effectiveness diminishes as the graphs ...

📝 Overview This project implements a Convolutional Neural Network (CNN) for binary image classification. The model features automated data preprocessing, GPU optimization, and comprehensive ...

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For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light instead of electricity to process information—promise faster speeds and ...

Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...

Binary News Network is a Content Syndication Platform that allows businesses or proprietary newswires to bring visibility to their content by syndicating it to premium, high-visibility networks ...

Binary News Network is a Content Syndication Platform that allows businesses or proprietary newswires to bring visibility to their content by syndicating it to premium, high-visibility networks ...

The tumor suppressor p53 is a transcription factor that controls the expression of hundreds of genes. Emerging evidence suggests that the p53-induced RNA-binding protein ZMAT3 is a key splicing ...