IEEE

Multi-Modal Graph Neural Networks for Physiological Signal Analysis

Abstract: A critically important application for physiological signal analysis lies in very early diagnosis and monitoring of potential medical conditions: among others, in cardiac dysfunction. This ...
IEEE

An Artificial Immune System Algorithm for the Permutation Flow Shop Scheduling Problem with Sequence Dependent Setup Times

Abstract: This paper is concerned with a set of independent jobs in a permutation flow shop that have setup times on a set of machines. The M-IAIS algorithm, which is based on immunoglobulins and has ...
IEEE

Control Mode Switching-Enabled Physics- Guided Multiagent Graph Learning for Real-Time AC/DC Power Flow

Abstract: Existing ac/dc power flow computations necessitate sequential convergence-oriented trial-and-error under various dc control modes, rising computational ...
IEEE

Graph Convolutional Network with Local Topology and Spectral Feature Representation for Multispectral Point Cloud Classification

Abstract: Multispectral LiDAR contributes to the rapid acquisition of 3D spatial and spectral information of land covers, providing more comprehensive features for classification. Despite the ...
IEEE

A Radar Signal Open-Set Deinterleaving Method Based on Laplacian Pyramid Reconstruction and Adversarial Reciprocal Point Learning

Abstract: Radar signal deinterleaving is a challenging task in complex electromagnetic environments. This work proposes a method for accurately deinterleaving known and unknown radar radiation sources ...
IEEE

Music-based Graph Convolution Neural Network with ECG, Respiration, Pulse Signal as a Diagnostic Tool for Hypertension

Abstract: Hypertension is one of the prime risk factors of cardiovascular disease. Music has been shown to be beneficial for lowering blood pressure. Here, we investigate if music can help in ...
IEEE

Enhancing EEG Motor Imagery Time Point Signal Classification through Reinforcement Learning and Graph Neural Networks

Abstract: Brain-Computer Interfaces (BCIs) rely on accurately decoding electroencephalography (EEG) motor imagery (MI) signals for effective device control. Graph Neural Networks (GNNs) outperform ...
IEEE

Petri net-based QUBO Model Formulation for Multi-Resource Flow-Shop Scheduling Problems

Abstract: This paper introduces a Petri net-based approach to addressing multi-resource flow-shop scheduling problems within multi-objective quantum optimization. The multi-resource flow-shop problem, ...
IEEE

Multi-Person Pose Tracking With Sparse Key-Point Flow Estimation and Hierarchical Graph Distance Minimization

Abstract: In this paper, we propose a novel framework for multi-person pose estimation and tracking on challenging scenarios. In view of occlusions and motion blurs which hinder the performance of ...
Benzinga.com

Google's Gemini Eating ChatGPT's Lunch: Market Share Gain From 5% To 18% Is 'Clearest Signal' That Alphabet Is Winning AI War

New data from Similarweb reveals a dramatic reshaping of the AI landscape. Over the last 12 months, Google's Gemini has more than tripled its slice of generative AI web traffic, climbing from a modest ...
IEEE

Multi-modal Dynamic Point Cloud Geometric Compression Based on Bidirectional Recurrent Scene Flow*

Abstract: Deep learning methods have recently shown significant promise in compressing the geometric features of point clouds. However, challenges arise when consecutive point clouds contain holes, ...
IEEE

Optimizing Access Point Placement in Industrial IoT: A Deep Reinforcement Learning Approach With Q-Learning Verification and Signal Heatmap Visualization

Abstract: Optimal access point (AP) placement inside an industrial layout is important to ensure excellent connectivity. However, wireless fidelity (Wi-Fi) AP placement is complicated because ...