Cues predictive of target locations orient covert attention, improving perceptual performance. Studies have focused on attentional influences on neural activity, but how cues activate attention and ...

This project investigates the application of Deep Neural Networks (DNNs) for automated fault classification and fault location in power transmission lines. Using data generated from a simulated 4-bus ...

Department of Pharmaceutics, College of Pharmacy, University of Florida, Gainesville, Florida 32610, United States Department of Medicinal Chemistry, College of Pharmacy, University of Florida, ...

Abstract: Recently, there has been a sharp rise in demand for hardware implementations because of the improved accuracy of Convolutional Neural Networks (CNN) on a wide range of classification and ...

This paper discusses a machine learning approach for detecting SSVEP at both ears with minimal channels. SSVEP is a robust EEG signal suitable for many BCI applications. It is strong at the visual ...

Videos of animal behavior are used to quantify researcher-defined behaviors of interest to study neural function, gene mutations, and pharmacological therapies. Behaviors of interest are often scored ...

This demo shows how to interpret the classification by CNN using LIME (Local Interpretable Model-agnostic Explanations) [1]. This demo was created based on [1], but the implementation might be a ...

Machine learning is a promising approach to evaluate human movement based on wearable sensor data. A representative dataset for training data-driven models is crucial to ensure that the model ...

Background: Convolution neural networks (CNN) is increasingly used in computer science and finds more and more applications in different fields. However, analyzing brain network with CNN is not ...