Dynamic Hierarchical Reinforcement Learning Framework for Energy-Efficient 5G Base Stations in Urban Environments
The energy consumption of 5G base stations (BSs) is significantly higher than that of 4G BSs, creating challenges for operators due to […]
MDANet: Modality-Aware Domain Alignment Network for Visible-Infrared Person Re-Identification
Visible-infrared person re-identification is a challenging task in video surveillance. Most existing works achieve performance gains by aligning feature distributions or image […]
DMANet: Dual-modality alignment network for visible-infrared person re-identification
Discovering attention-guided cross-modality correlation for visible–infrared person re-identification
Visible–infrared person re-identification (VI Re-ID) is an essential and challenging task. Existing studies mainly focus on learning the unified modality-invariant representations directly […]
Toward Efficient Fire Detection in IoT Environment: A Modified Attention Network and Large-Scale Data Set
Multi-Resolution LSTM-Based Prediction Model for Remaining Useful Life of Aero-Engine
Aircraft is an important means of travel and the most convenient and fast vehicle in long-distance transportation. The aircraft engine is one […]
End-to-End Dual-Branch Network Towards Synthetic Speech Detection
Synthetic speech attacks bring more threats to Automatic Speaker Verification (ASV) systems, thus many synthetic speech detection (SSD) systems have been proposed […]
A Multi-Stream Feature Fusion Approach for Traffic Prediction
Accurate and timely traffic flow prediction is crucial for intelligent transportation systems (ITS). Recent advances in graph-based neural networks have achieved promising […]