Language Independent Query by Example Spoken Term Detection

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This paper introduces MNE-RT, a Python package designed for real-time neural feature extraction from magne-toencephalography (MEG) and electroencephalography (EEG) signals in Brain-Computer Interface (BCI) systems. The package incorporates efficient algori ...

Rigid body interactions are fundamental to numerous scientific disciplines, but remain challenging to simulate due to their abrupt nonlinear nature and sensitivity to complex, often unknown environmental factors. These challenges call for adaptable learnin ...

Dynamic aperture is an important concept for the study of non-linear beam dynamics in circular accelerators. It describes the extent of the phase-space region where a particle's motion remains bounded over a given number of turns. Understanding the feature ...

The Internet of Things (IoT) consists of physical objects and devices embedded with network connectivity, software, and sensors to collect and transmit data. The development of the Internet of Things (IoT) has led to various security and privacy issues, in ...

The present work proposes a framework for nonlinear model order reduction based on a Graph Convolutional Autoencoder (GCA-ROM). In the reduced order modeling (ROM) context, one is interested in obtaining real -time and many-query evaluations of parametric ...

Thermal scene reconstruction holds great potential for various applications, such as building energy analysis and non-destructive infrastructure testing. However, existing methods rely on dense scene measurements and use RGB images for 3D reconstruction, i ...

This study examines the acoustic features of Parkinson's patients with depression. More specifically, the research investigates whether interpretable, handcrafted acoustic feature-based methods, previously used for automatic speech-based depression detecti ...

Clustering in education, particularly in large-scale online environments like MOOCs, is essential for understanding and adapting to diverse student needs. However, the effectiveness of clustering depends on its interpretability, which becomes challenging w ...

The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power. Simultaneously, a critical pain point arises as several computer vision applications are deploye ...

Language Independent Query by Example Spoken Term Detection

Chat with Graph Search

Advances on Real Time M/EEG Neural Feature Extraction

Integrating Physics and Topology in Neural Networks for Learning Rigid Body Dynamics

Optimizing Dynamic Aperture Studies with Active Learning

GraphFedAI framework for DDoS attack detection in IoT systems using federated learning and graph based artificial intelligence

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

ThermoNeRF: A multimodal Neural Radiance Field for joint RGB-thermal novel view synthesis of building facades

Exploring the Complexity of Parkinson's Patient Speech for Depression Detection task: A Qualitative Analysis

Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation