Abstract: In recent years, uncrewed aerial vehicle (UAV) technology has shown great potential for application in hyperspectral image (HSI) classification tasks due to its advantages of flexible ...
Abstract: Improving the resolution of medical images is an important task in ensuring trustworthy diagnosis and effective monitoring of diseases. Of the newest deep learning algorithms, Convolutional ...
Abstract: The escalating scale and sophistication of cyberattacks pose a formidable challenge to conventional intrusion detection systems (IDS) because they lack the flexibility to adapt to evolving ...
Abstract: The CT Kidney Dataset is a structured and medically significant collection of Computed Tomography (CT) scan images, curated for the i m p ro v em en t and growth of AI-predicted diagnostic ...
CEOs must put projects, not operations, at the center of how their companies create value. Here’s how. by Antonio Nieto-Rodriguez In an environment of constant change, projects are how businesses ...
Abstract: The Deepfake Face Image Detection System uses Convolutional Neural Networks (CNNs) to address the growing threat of deepfakes, which manipulate images to falsely depict events or actions, ...
Abstract: Magnetic resonance imaging (MRI) is an important tool for brain cancer diagnosis and classification. Combined with modern convolutional neural network (CNN) technology, it can effectively ...
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New renderings shared Friday offer the clearest look yet at President Donald Trump’s proposed White House ballroom addition — a project advancing even as it is challenged in court and questioned on ...
Abstract: The UC Merced (UCM) land use dataset is a widely adopted benchmark for evaluating aerial image classification algorithms. This paper presents a comparative performance analysis of prominent ...
The Python extension now supports multi-project workspaces, where each Python project within a workspace gets its own test tree and Python environment. This document explains how multi-project testing ...