Abstract: This work introduces a robust hybrid CNN-LSTM framework designed for the reliable identification and categorization of epileptic seizures using electroencephalogram (EEG) signals. The model ...
Abstract: Deepfake technology, using deep learning, creates highly realistic yet artificial media, creating challenges for security and privacy. Convolutional Neural Networks (CNNs) play a crucial ...
Abstract: Anaemia is a condition marked by an insufficient number of healthy red blood cells, often initially indicated through visible conjunctival pallor. Conventional diagnostic approaches rely on ...
Abstract: Our study addresses the shortcomings of existing methods by designing a software-based spoofing-signal identification system for civilian GNSS receivers, enabling intelligent detection of ...
Abstract: Finding ships in water using high-resolution radar images is goal of synthetic aperture radar (SAR) ship detection, which works in any lighting or weather scenario. By taking advantage of ...
Abstract: Monocular 3D object detection has gained considerable attention because of its cost-effectiveness and practical applicability, particularly in autonomous driving and robotics. Most of ...
Abstract: Remote sensing platforms provide crucial data for applications such as urban planning and traffic monitoring. However, detecting small objects remains challenging due to low resolution, ...
Abstract: With the proliferation of social media platforms, where users are free to express themselves and share content, the detection of fake news in text has become an important issue. The ...
Abstract: Small object detection in UAV aerial imagery presents significant challenges due to limited pixel coverage and complex backgrounds. This paper introduces DPLR-DETR (Dynamic Position Large ...