Abstract: This work introduces EffiSegNet, a novel segmentation framework leveraging transfer learning with a pre-trained Convolutional Neural Network (CNN) classifier as its backbone. Deviating from ...
Abstract: This article introduces a comprehensive multiagent prototype system designed to enhance the autonomous navigation capabilities of vehicles by incorporating numerous sensors and components.
Abstract: Real-time fault detection and classification are important for power system stability and resilience of the power grid to minimize downtime and prevent cascading failures. Numerical relays ...
Abstract: This study aims to classify brainwave patterns using electroencephalogram (EEG) signals in response to various auditory stimuli, specifically Quran recitation, participants’ favorite music, ...
Abstract: Due to the increased use of social networks, word-of-mouth analysis has become an effective tool in market research since firms can determine the users’ attitudes toward their brands.
Abstract: As AI technology evolves, seeing is not believing. The boundary between human and machine creativity is increasingly blurred, presenting challenges for the art industry. This is more ...
Abstract: The field of information fusion and deep learning (DL) has advanced significantly in recent years, enabling computers and other devices to perceive, recognize, and evaluate emotions. In ...
This project is a Convolutional Neural Network (CNN)-based image classifier designed to distinguish between images of cats and dogs. It includes a complete training pipeline and a Flask-based web ...
Abstract: As Deep Learning (DL) algorithms become more widely adopted in healthcare applications, there is a greater emphasis on understanding and addressing potential privacy risks associated with ...
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