Abstract: In recent years, crowd counting has garnered increasing attention due to its wide range of societal applications. However, the vast differences in crowd density distributions across various ...

Abstract: Hyperspectral anomaly detection (HAD) is challenging especially when anomalies appear in the form of subpixels. Since the spectral signatures of anomalies in mixed pixels are mixed with ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=4 ...

Abstract: Automatic medical image segmentation is a crucial topic in the medical domain and successively a critical counterpart in the computer-aided diagnosis paradigm. U-Net is the most widespread ...

Abstract: This paper investigates the problem of interval state and attack signal estimation and fault tolerant consistent control in multi-agent systems under the influence of deception attacks.

Abstract: Multi-view learning has raised more and more attention in recent years. However, traditional approaches only focus on the difference while ignoring the consistency among views. It may make ...

Abstract: This paper presents a cooperative multi-agent deep reinforcement learning (MADRL) approach for unmmaned aerial vehicle (UAV)-aided mobile edge computing (MEC) networks. An UAV with computing ...

Abstract: The four-switch flyback (FSF) converter has the advantages of low switch voltage stress and zero-voltage-switching (ZVS) with the leakage inductance energy. However, if the clamping ...

Abstract: The widespread adoption of the fifth generation (5G) of cellular networks has brought new opportunities for the development of localization-based services. High-accuracy positioning use ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=34 ...

Abstract: Due to the absence of a gold standard for threshold selection, brain networks constructed with inappropriate thresholds risk topological degradation or contain noise connections. Therefore, ...