IEEE

Toward Visual Interaction: Hand Segmentation by Combining 3-D Graph Deep Learning and Laser Point Cloud for Intelligent Rehabilitation

Abstract: Against the backdrop of the increasing trend of aging population in China and even globally, the demand for hand function rehabilitation is growing day by day, and human-machine interaction ...
Scientific Research Publishing

Open Flow Controller Architecture for Seamless Connectivity and Virtualization Technologies ()

Nicola, A.A. (2026) Open Flow Controller Architecture for Seamless Connectivity and Virtualization Technologies.
IEEE

Rethinking Variational Bayes in Community Detection From Graph Signal Perspective

Abstract: Methods based on variational bayes theorytare widely used to detect community structures in networks. In recent years, many related methods have emerged that provide valuable insights into ...
IEEE

Energy Efficiency Optimization with Machine Activation in Blocking Hybrid Flow Shop Scheduling Problem

Abstract: This study tackles the blocking hybrid flow-shop scheduling problem (BHFSP), focusing on minimizing energy consumption. Unlike traditional problems, we consider machine standby, setup modes, ...
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 ...
IEEE

Visual Evolutionary Optimization on Graph-Structured Combinatorial Problems With MLLMs: A Case Study of Influence Maximization

Abstract: Graph-structured combinatorial problems in complex networks are prevalent in many domains, and are computationally demanding due to their complexity and non-linear nature. Traditional ...
IEEE

Dynamic Graph Convolutional Recurrent Network With Spatiotemporal Category Information Embedding for Traffic Flow Prediction

Abstract: Traffic flow prediction is a challenging spatiotemporal prediction task due to its spatiotemporal dynamics and uncertainty. In recent years, graph convolutional neural networks (GCNs) have ...