Super resolution (SR) and fast magnetic resonance (MR) imaging play a paramount role in medical diagnosis community. Though significant progress has been achieved, existing methods are mostly trapped at the local feat...
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The training method of Spiking Neural Networks (SNNs) is an essential problem, and how to integrate local and global learning is a worthy research interest. However, the current integration methods do not consider the...
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Electronic Health Record (EHR) systems have replaced paper-based systems in healthcare organizations. There are now many measures in the medical field to protect sensitive big data. However, the healthcare industry is...
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The complexity of scenes and the topology of cracks make road crack detection a challenging task. Compared to other semantic segmentation tasks, this mission places a greater demand on the network's ability to pre...
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In modern vision-based robot grasping inspection systems, the effective fusion of color image and depth image is very important to improve the accuracy and robustness of the system. Traditional grasp detection methods...
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Soft magnetic material with high saturation magnetization(Ms)and high resistance(ρ)is vital to improve the power density and conversion efficient of modern electrical magnetic ***,increasing Ms is always at the expen...
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Soft magnetic material with high saturation magnetization(Ms)and high resistance(ρ)is vital to improve the power density and conversion efficient of modern electrical magnetic ***,increasing Ms is always at the expense of high resistivity,such as soft magnetic alloys substitute for the *** this work,the superior comprehensive electromagnetic properties,namely the close association of high saturation magnetization and high resistivity,are combined in a new way in a newly Fe-N based magnetic materials.A high resistance oxide interface engineering was constructed between the conducting ferromagnetic phases in the process of spark plasma sintering(SPS)to achieve superior electromagnetic *** ZnO compositeγ’-Fe_(4) N bulk has a maximum resistivity of 220μΩ cm and a Ms of up to 156.02 emu/g,while the TiO_(2)compositeγ’-Fe_(4) N bulk has a maximum resistivity of 379μcm and a Ms of 149.7 emu/*** research findings offer valuable insights for the advancement of the next generation of soft magnetic materials,which hold significant potential for use in high-frequency,high-efficiency,and energy-saving power equipment applications.
In human pose estimation in complex scenes, the complexity of background and foreground increases, and the existing attention mechanism is generally unable to effectively capture the spatial position information of hu...
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As an emerging technology, quantum networks have the potential to revolutionize secure communication and data transmission technologies. In the Noisy Intermediate-Scale Quantum (NISQ) era, quantum noise causing low fi...
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Recommender systems are effective in mitigating information overload, yet the centralized storage of user data raises significant privacy concerns. Cross-user federated recommendation(CUFR) provides a promising distri...
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Recommender systems are effective in mitigating information overload, yet the centralized storage of user data raises significant privacy concerns. Cross-user federated recommendation(CUFR) provides a promising distributed paradigm to address these concerns by enabling privacy-preserving recommendations directly on user devices. In this survey, we review and categorize current progress in CUFR, focusing on four key aspects: privacy, security, accuracy, and efficiency. Firstly,we conduct an in-depth privacy analysis, discuss various cases of privacy leakage, and then review recent methods for privacy protection. Secondly, we analyze security concerns and review recent methods for untargeted and targeted *** untargeted attack methods, we categorize them into data poisoning attack methods and parameter poisoning attack methods. For targeted attack methods, we categorize them into user-based methods and item-based methods. Thirdly,we provide an overview of the federated variants of some representative methods, and then review the recent methods for improving accuracy from two categories: data heterogeneity and high-order information. Fourthly, we review recent methods for improving training efficiency from two categories: client sampling and model compression. Finally, we conclude this survey and explore some potential future research topics in CUFR.
Object detection is an important task in drone vision. Since the number of objects and their scales always vary greatly in the drone-captured video, small object-oriented feature becomes the bottleneck of model perfor...
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Object detection is an important task in drone vision. Since the number of objects and their scales always vary greatly in the drone-captured video, small object-oriented feature becomes the bottleneck of model performance, and most existing object detectors tend to underperform in drone-vision scenes. To solve these problems, we propose a novel detector named YOLO-Drone. In the proposed detector, the backbone of YOLO is firstly replaced with ConvNeXt, which is the state-of-the-art one to extract more discriminative features. Then, a novel scale-aware attention(SAA) module is designed in detection head to solve the large disparity scale problem. A scale-sensitive loss(SSL) is also introduced to put more emphasis on object scale to enhance the discriminative ability of the proposed detector. Experimental results on the latest VisDrone 2022 test-challenge dataset(detection track) show that our detector can achieve average precision(AP) of 39.43%, which is tied with the previous state-of-the-art, meanwhile,reducing 39.8% of the computational cost.
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