The research, titled AI-Driven Hybrid Deep Learning and Swarm Intelligence for Predictive Maintenance of Smart Manufacturing Robots in Industry 4.0 and published in Electronics, introduces an AI ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...
This valuable study uses mathematical modeling and analysis to address the question of how neural circuits generate distinct low-dimensional, sequential neural dynamics that can change on fast, ...
In this article, the authors investigated how the brain anticipates sequences of potential sensory events, using temporal predictability to enhance perception. To do so, they combined a tone detection ...
Introduction: As the number of Internet of Things (IoT) devices grows quickly, cyber threats are becoming more complex and increasingly sophisticated; thus, we need a more robust network security ...
1 KNDS Deutschland GmbH & Co. KG, Munich, Germany 2 Institute for Software Technology, University of the Bundeswehr Munich, Neubiberg, Germany Artificial intelligence (AI) has emerged as a ...
The global energy sector is undergoing a transformation, with the electric grid expanding to accommodate an increasing number of assets, including solar arrays, wind farms, batteries, electric ...
Behavioral Classification of Sequential Neural Activity Using Time Varying Recurrent Neural Networks
Abstract: Shifts in data distribution across time can strongly affect early classification of time-series data. When decoding behavior from neural activity, early detection of behavior may help in ...
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