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 ...
Abstract: One of the most critical neurological conditions is Brain tumors, timely and correct diagnosis is needed for effective treatment. Advances in neuroimaging technology such as MRI, limitations ...
Abstract: A research project focuses on creating automated trash detection and classification through convolutional neural networks (CNNs) with an objective to improve waste management systems. The ...
Abstract: This letter proposes KAN-based multispectral image super-resolution method (KMSR), a novel deep learning framework for multispectral image (MSI) super-resolution (SR) that integrates ...
CrashFix crashes browsers to coerce users into executing commands that deploy a Python RAT, abusing finger.exe and portable Python to evade detection and persist on high‑value systems.
Abstract: Pneumonia is one of the most serious lung infections and remains a leading cause of death in children under five years of age, especially in developing countries such as Indonesia. Diagnosis ...
Democrats notched another victory Saturday in special elections during President Donald Trump’s second term, flipping a seat in the Texas Senate that Trump won by 17 points in 2024. Taylor Rehmet, a ...
Abstract: With the advancement of autonomous driving technologies, passengers increasingly engage in non-driving activities. However, these activities are often limited by motion sickness (MS), which ...
Hyperspectral image (HSI) classification aims at categorizing each pixel in an HSI, facilitating precise identification and differentiation of various land cover types. In recent years, graph neural ...
Abstract: In remote sensing (RS), convolutional neural networks (CNNs) are well-recognized for their spatial–spectral feature extraction capabilities, whereas vision transformers (ViTs), which ...
Abstract: Timely and accurate identification of plant diseases is essential for sustainable agricultural practices and food security. This study presents a deep learning-based diagnostic framework ...
Abstract: Global surface changes are increasingly monitored using multi-temporal remote sensing technologies. As an emerging technology, change captioning can organically integrate the location ...
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