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오늘 본 자료
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Development of a flight test system for unmanned air vehicles
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Safety implication of Salmonella based Brucella vaccine candidate in mice and in vitro human cell culture
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(주) 기분좋은 커뮤니케이션
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Laparoscopic ultrasonography in assessment of resectability in patients with upper gastrointestinal malignancies
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IEEE 802.11x 무선 랜 네트워크에서 전송률 향상을 위한 다중 중계기 협력 통신
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- 저자 : Zongwen Wang (검색결과 3 건)
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A Novel Cross-Layer Dynamic Integrated Priority-Computing Scheme for 3G+ Systems
Wang, Weidong,Wang, Zongwen,Zhao, Xinlei,Zhang, Yinghai,Zhou, Yao The Korea Institute of Information and Commucation 2012 Journal of communications and networks Vol.14 No.1
As Internet protocol and wireless communications have developed, the number of different types of mobile services has increased gradually. Existing priority-computing schemes cannot satisfy the dynamic requirements of supporting multiple services in future wireless communication systems, because the currently used factors, mainly user priority, are relatively simple and lack relevancy. To solve this problem and provide the desired complexity, dynamic behavior, and fairness features of 3G and beyond 3G mobile communication systems, this paper proposes a novel cross-layer dynamic integrated priority-computing scheme that computes the priority based on a variety of factors, including quality of service requirements, subscriber call types, waiting time, movement mode, and traffic load from the corresponding layers. It is observed from simulation results that the proposed dynamic integrated priority scheme provides enhanced performance.
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A Novel Cross-Layer Dynamic Integrated Priority-Computing Scheme for 3G+ Systems
Weidong Wang,Zongwen Wang,Xinlei Zhao,Yinghai Zhang,Yao Zhou 한국통신학회 2012 Journal of communications and networks Vol.14 No.1
As Internet protocol and wireless communications have developed, the number of different types of mobile services has increased gradually. Existing priority-computing schemes cannot satisfy the dynamic requirements of supporting multiple services in future wireless communication systems, because the currently used factors, mainly user priority, are relatively simple and lack relevancy. To solve this problem and provide the desired complexity,dynamic behavior, and fairness features of 3G and beyond 3G mobile communication systems, this paper proposes a novel crosslayer dynamic integrated priority-computing scheme that computes the priority based on a variety of factors, including quality of service requirements, subscriber call types, waiting time, movement mode, and traffic load from the corresponding layers. It is observed from simulation results that the proposed dynamic integrated priority scheme provides enhanced performance.
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A Novel Two-Stage Training Method for Unbiased Scene Graph Generation via Distribution Alignment
Dongdong Jia,Meili Zhou,Wei Wei,Dong Wang,Zongwen Bai 한국인터넷정보학회 2023 KSII Transactions on Internet and Information Syst Vol.17 No.12
Scene graphs serve as semantic abstractions of images and play a crucial role in enhancing visual comprehension and reasoning. However, the performance of Scene Graph Generation is often compromised when working with biased data in real-world situations. While many existing systems focus on a single stage of learning for both feature extraction and classification, some employ Class-Balancing strategies, such as Re-weighting, Data Resampling, and Transfer Learning from head to tail. In this paper, we propose a novel approach that decouples the feature extraction and classification phases of the scene graph generation process. For feature extraction, we leverage a transformer-based architecture and design an adaptive calibration function specifically for predicate classification. This function enables us to dynamically adjust the classification scores for each predicate category. Additionally, we introduce a Distribution Alignment technique that effectively balances the class distribution after the feature extraction phase reaches a stable state, thereby facilitating the retraining of the classification head. Importantly, our Distribution Alignment strategy is model-independent and does not require additional supervision, making it applicable to a wide range of SGG models. Using the scene graph diagnostic toolkit on Visual Genome and several popular models, we achieved significant improvements over the previous state-of-the-art methods with our model. Compared to the TDE model, our model improved mR@100 by 70.5% for PredCls, by 84.0% for SGCls, and by 97.6% for SGDet tasks.
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