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- Crowd Counting and Density Estimation by Trellis Encoder-Decoder Networks366
This paper proposes a trellis encoder-decoder network (TEDnet) for crowd counting that achieves the best overall performance in terms of both density map quality and counting accuracy, and proposes a new combinatorial loss to enforce similarities in local coherence and spatial correlation between maps.
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- Few-Shot Semantic Segmentation with Democratic Attention Networks241
This paper introduces the de-mocratized graph attention mechanism, which can activate more pixels on the object to establish a robust correspondence between support and query images, and proposes multi-scale guidance by designing a refinement fusion unit to fuse features from intermediate layers for the segmentation of the query image.
- Realizing the Metaverse with Edge Intelligence: A Match Made in Heaven238
The architecture of the Metaverse is discussed and mainly focus on motivating the convergence of edge intelligence and the infrastructure layer of theMetaverse, and major edge-based technological developments and their integration to support the metaverse engine are presented.
- Millimeter-Wave NOMA With User Grouping, Power Allocation and Hybrid Beamforming230
The proposed joint approach, including user grouping, hybrid beamforming and power allocation, outperforms the state-of-the-art schemes and the conventional mmWave orthogonal multiple access system in terms of achievable sum rate, and energy efficiency.
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- Trajectory Design for UAV-Based Internet of Things Data Collection: A Deep Reinforcement Learning Approach185
An unmanned aerial vehicle (UAV)-assisted Internet of Things (IoT) system in a sophisticated 3-D environment, where the UAV’s trajectory is optimized to efficiently collect data from multiple IoT ground nodes, and presents a TD3-based trajectory design for completion time minimization (TD3-TDCTM) algorithm.
- Evolution of Chinese airport network182
It is found that although the topology of CAN has remained steady during the past few years, there are many dynamic switchings inside the network, which have changed the relative importance of airports and airlines.
- Millimeter-Wave Full-Duplex UAV Relay: Joint Positioning, Beamforming, and Power Control178
Simulation results confirm the superiority of the proposed positioning, beamforming, and power control method compared to three benchmark schemes and show that the proposed solution closely approaches a performance upper bound for mmWave FD-UAV systems.
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- Path Planning for Single Unmanned Aerial Vehicle by Separately Evolving Waypoints144
The original objective and constraint functions of UAVs path planning are decomposed into a set of new evaluation functions, with which waypoints on a path can be evaluated separately and, thus, high-quality waypoints can be better exploited.
- Semantic Communication Meets Edge Intelligence142
This article introduces an edge-driven training, maintenance, and execution of semantic extraction (SE), and investigates how edge intelligence can be enhanced with SemCom through improving the generalization capabilities of intelligent agents at lower computation overheads and reducing the communication overhead of information exchange.
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- Improving the network robustness against cascading failures by adding links136
Three link-adding strategies are compared and it is found that HBS is more effective than RLS to enhance the network robustness against cascades while the network exhibits the strongest robustness under LPS.
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- Joint Power Control and Beamforming for Uplink Non-Orthogonal Multiple Access in 5G Millimeter-Wave Communications107
This paper investigates the combination of two key enabling technologies for the fifth generation wireless mobile communication, namely millimeter-wave (mm-wave) communications and non-orthogonal multiple access (NOMA), and proposes an analog beamforming problem under a constant-modulus constraint.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-16. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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