检索结果-内蒙古大学图书馆

International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Zheng Ti Xuze Hao Renhai Chen College of Intelligence and Computing Tianjin University Tianjin China School of Computer Science Shanghai Key Laboratory of Intelligent Information Processing Fudan University China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Continual Semantic Segmentation (CSS) aims to continuously learn new classes while mitigating catastrophic forgetting. Existing CSS methods primarily address this challenge through knowledge distillation. While they focus on maintaining stability for old classes, this emphasis often restricts plasticity in learning new ones. In this work, we propose two plug-and-play methods to better balance stability and plasticity. First, for feature map distillation, we replace pixel-level constraints with statistical information extraction within a window, improving the learning of new classes while preserving structural integrity to overcome forgetting. Second, we use relative ranks of predictions to replace exact probabilistic values to loosen the constraints in the logit distribution of old classes. Extensive experiments demonstrate that our methods outperform state-of-the-art methods when integrating into several baselines across various CSS scenarios.

关键词： Semantic segmentation Semantics Signal processing Feature extraction Probabilistic logic information retrieval Acoustics Data mining Speech processing

来源：评论

学校读者我要写书评

暂无评论

Dual-layer Broadband High-gain Circularly Polarized Patch Antenna with L-shaped Stub

Dual-layer Broadband High-gain Circularly Polarized Patch An...

引用

2023 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition, iWEM 2023

作者： Li, Wen Xue, Wei Li, Yingsong Loh, Tian Hong Chung, Kwok L. Harbin Engineering University College of Information and Communication Engineering Harbin150001 China Anhui University The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Hefei China National Physical Laboratory Electromagnetic and Eletrochemical Technologies Department Middlesex United Kingdom Huizhou University School of Computing Science and Engineering Huizhou516007 China

ISBN: (纸本)9798350336740

This paper introduced a dual-layer broadband high-gain circularly polarized (CP) antenna. The proposed broadband CP antenna consists of the radiating patch and couping structure, which is made up of opening slot patch and L-shaped stub. An axial-ratio bandwidth of 26 % (4.36-5.66 GHz) is shown by this proposed dual-layer CP patch antenna with a simulated -10-dB reflection coefficient bandwidth of 37 % (4.23-6.15 GHz). The broadband characteristics offered by this CP antenna are promising for a wide range of future applications. © 2023 IEEE.

关键词： Microstrip antennas

来源：评论

学校读者我要写书评

暂无评论

Lightweight Single Image Super-Resolution Network Integrating CNN and Transformer 27th

Lightweight Single Image Super-Resolution Network Integratin...

引用

27th International Conference on Pattern Recognition, ICPR 2024

作者： Zhu, Kai Chen, Li School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)9783031781247

Recently, remarkable progress has been achieved in single image super-resolution using methods based on CNN and Transformer architectures. However, existing approaches often construct a substantial number of network layers, leading to a significant increase in performance requirement and memory consumption, thereby limiting the practical deployment and usability of the models. To address this issue, we propose an Alternating CNN Transformer Block and an Integrative CNN Efficient Transformer for single image super-resolution. We enhance feature extraction efficiency by combining CNN within and between Transformer modules. In addition, we propose two novel structures: Multi-branch Gated CNN and Parallel Channel Attention, aiming to efficiently extract local spatial information and global channel information from images. Extensive experiments demonstrate that our model achieves high performance while maintaining low model complexity. The proposed model attains PSNR values of 32.32 and 30.78 for the Set5 and Manga109 benchmark datasets, respectively, at a scale factor of ×4. Compared to other lightweight super-resolution models, our proposed model outperforms them at lower computational costs. The source codes are available at https://***/kylechuuuuu/ICTSRN. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： HTTP

来源：评论

学校读者我要写书评

暂无评论

SIGAN: Self-inhibited Graph Attention Network for Text Classification 1

引用

23rd International Conference on intelligent Systems Design and Applications, ISDA 2023

作者： Fang, Jiaqi Ma, Kun School of Information Science and Engineering University of Jinan Jinan250022 China Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Jinan250022 China Quancheng Laboratory Shandong Jinan250103 China

ISBN: (数字)9783031647796

ISBN: (纸本)9783031647789

Text classification is a pivotal task within the field of natural language processing (NLP) that has many practical applications. However, there are several challenges of existing methods of Graph Convolutional Networks, such as difficulties in capturing long-range dependencies and overfitting issues. To address these challenges, we have proposed a novel model called Self-Inhibited Graph Attention Network (abbreviated as SIGAN), which builds upon the foundation of TextGCN but introduces two key contributions: Graph Attention Networks (GATs) and Self-Inhibition Structure (SIS). GATs enable adaptive weight allocation to nodes, facilitating a better understanding of complex relationships within graph data, including long-distance dependencies;SIS replaces the Dropout operation used in TextGCN and preserves the overfitting prevention properties of Dropout while avoiding the loss of crucial features by considering the importance levels of individual neurons. Our model is evaluate on four large-scale datasets (R52, MR, R8, Ohsumed), and we compare our methods with several baselines such as TextGCN and TWPGCN. Our results show that SIGAN achieves better improvements in accuracy, with gains of 0.93%, 1.27%, 0.88%, and 0.39%, respectively. Experimental results show the effectiveness of the model enhancements and the structure of self-inhibition. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Large datasets

来源：评论

学校读者我要写书评

暂无评论

SCENERY:a lightweight block cipher based on Feistel structure

引用

Frontiers of Computer Science 2022年第3期16卷 193-202页

作者： Jingya FENG Lang LI Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang Normal UniversityHengyang 421002China College of Information Science and Engineering Hunan Normal UniversityChangsha 410081China College of Computer Science and Technology Hengyang Normal UniversityHengyang 421002China

In this paper,we propose a new lightweight block cipher called *** main purpose of SCENERY design applies to hardware and software *** is a 64-bit block cipher supporting 80-bit keys,and its data processing consists of 28 *** round function of SCENERY consists of 84×4 S-boxes in parallel and a 32× 32 binary matrix,and we can implement SCENERY with some basic logic *** hardware implementation of SCENERY only requires 1438 GE based on 0.18 um CMOS technology,and the software implementation of encrypting or decrypting a block takes approximately 1516 clock cycles 0118-bit microcontrollers and 364 clock cycles on 64-bit *** with other encryption algorithms,the performance of SCENERY is well balanced for both hardware and *** the security analyses,SCENERY can achieve enough security margin against known attacks,such as differential cryptanalysis,linear cryptanalysis,impossible differential cryptanalysis and related-key attacks.

关键词： lightweight block cipher feistel structure cryptanalysis internet of things

来源：评论

学校读者我要写书评

暂无评论

Blockchain-based Transaction Scheme for Massive MIMO Channel Estimation 11

Blockchain-based Transaction Scheme for Massive MIMO Channel...

引用

11th International Conference on Networks, Communication and computing, ICNCC 2022

作者： Huang, Yu Zhi, Hui Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei230601 China School of Electronic and Information Engineering Anhui University Hefei230601 China

ISBN: (纸本)9781450398039

In wireless communication systems, accurate channel estimation is essential to ensure the performance of wireless communication systems. Massive Multiple Input Multiple Output (M-MIMO) systems have a dramatic increase in the number of channels to be estimated due to the large number of antennas, which poses a great challenge to the computing resources of the base station, and one solution is offloading these computing tasks of channel estimation to other computing nodes with more computing resources (such as servers). However, in real life, computing nodes are not willing to participate in channel estimation because of their equipment and operation cost. In order to solve this problem, this paper introduces blockchain technology and designs a blockchain-based transaction scheme for channel estimation (BTS-CE) to solve the problem of computing resources transaction for massive MIMO channel estimation, and designs the specific process of the scheme. In order to solve the problem that computing nodes cannot complete the computation task due to failure or malicious disconnection, a task allocation model is designed to assign a computation task to multiple computation nodes. The security of the transactions is guaranteed through the blockchain. Practical Byzantine Fault Tolerance (PBFT) consensus mechanism cannot be applied to the public chain due to its low performance caused by a large number of nodes participating in consensus, this problem is solved by selecting some active nodes as consensus nodes. Simulation results show that improved PBFT(IPBFT) is lower in transaction delay and higher in throughput than PoW consensus mechanism. © 2022 ACM.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

ASTGNN: Adaptive Spatio-Temporal Graph Neural Network for Motor Imagery Recognition

ASTGNN: Adaptive Spatio-Temporal Graph Neural Network for Mo...

引用

2024 International Conference on Mechatronics and intelligent Control, ICMIC 2024

作者： Zhao, Zheng Xue, Haixiao Huang, Yuwen Zhao, Qi Xie, Xin Dalian Maritime University Dalian China Northeastern University Shenyang China Hunan University of Information Technology Changsha China Hunan Province Higher Education Key Laboratory of Intelligent Sensing and Computing Changsha China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

Motor imagery electroencephalogram recognition is a key area in brain-computer interfaces, with applications in human-computer interaction, rehabilitation, and virtual reality. Traditional methods often overlook the brain's topological characteristics and the correlations between EEG channels, resulting in suboptimal decoding. To address this, we propose an adaptive spatio-temporal graph neural network (ASTGNN), which constructs a brain graph topology and adaptively learns the topological adjacency matrix, exploring both common and individual electrode connections. The spatial features are extracted using a graph convolutional network, while a gated position-aware self-attention mechanism captures movement information and global dependencies, enhancing temporal feature extraction. Experiments show that ASTGNN significantly improves recognition, achieving an average accuracy of 87.36%. © 2025 SPIE.

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

DTS: Dynamic Traffic Scrubbing Against Link Flooding Attacks with Programmable Data Plane

DTS: Dynamic Traffic Scrubbing Against Link Flooding Attacks...

引用

2024 International Conference on Mechatronics and intelligent Control, ICMIC 2024

作者： Zhao, Zheng Liu, Fang Meng, Zhaoran Zhao, Qi Xie, Xin Dalian Maritime University Dalian China Northeastern University Shenyang China Hunan University of Information Technology Changsha China Hunan Province Higher Education Key Laboratory of Intelligent Sensing and Computing Changsha China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

Link flood attacks (LFA) represent a significant cybersecurity threat due to their ability to cause extensive network disruptions. Traditional traffic scrubbing methods, relying on static rules, often struggle to counter dynamic LFAs effectively. This paper introduces the dynamic traffic scrubbing (DTS) method, leveraging programmable data planes. DTS integrates moving target defense principles into traffic scrubbing, dynamically deploying and adjusting scrubbing rules to thwart attackers. Game theory is employed to analyze the distributed denial of service attack and defense strategies. Experimental results demonstrate that DTS effectively mitigates dynamic LFAs with minimal overhead, showcasing its robustness in defending against sophisticated cyber threats. © 2025 SPIE.

关键词： Denial-of-service attack

来源：评论

学校读者我要写书评

暂无评论

Cross-Modal Ship Grounding: Towards Large Model for Enhanced Few-Shot Learning 27th

Cross-Modal Ship Grounding: Towards Large Model for Enhanced...

引用

27th International Conference on Pattern Recognition, ICPR 2024

作者： Hu, Quan Chen, Li Feng, Zhida Chen, Yaojie School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)9783031781124

A growing body of research indicates that employing large models for adaptation to downstream tasks often yields remarkable performance. However, in the domain of ship detection, the potential of these large models is frequently underutilized due to domain shift issues. This paper introduces the Cross-Modal Ship Grounding (CSG) model, which leverages an efficient Cross-Modal Adapter (CMA) technology to transfer the general detection capabilities of large models to ship images, addressing domain shift with minimal training costs. To mitigate the challenges posed by complex and variable background interference, the Water-Land Separation (WLS) module is proposed to focus specifically on the water area. This module effectively addresses the issue of background target interference, thereby enhancing the model’s accuracy in complex scenes. Empirical evaluations on both private and public datasets demonstrate that the CSG model surpasses all state-of-the-art models in performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Zero-shot learning

来源：评论

学校读者我要写书评

暂无评论

Side-channel analysis attacks based on deep learning network

引用

Frontiers of Computer Science 2022年第2期16卷 35-45页

作者： Yu OU Lang LI Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang Normal UniversityHengyang 421002China College of Information Science and Engineering Hunan Normal UniversityChangsha 410081China College of Computer Science and Technology Hengyang Normal UniversityHengyang 421002China

There has been a growing interest in the sidechannel analysis(SCA)field based on deep learning(DL)*** DL network or model has been developed to improve the efficiency of ***,few studies have investigated the impact of the different models on attack results and the exact relationship between power consumption traces and intermediate *** on the convolutional neural network and the autoencoder,this paper proposes a Template Analysis Pre-trained DL Classification model named TAPDC which contains three *** TAPDC model detects the periodicity of power trace,relating power to the intermediate values and mining the deeper features by the multi-layer convolutional *** implement the TAPDC model and compare it with two classical models in a fair *** evaluative results show that the TAPDC model with autoencoder and deep convolution feature extraction structure in SCA can more effectively extract information from power consumption ***,Using the classifier layer,this model links power information to the probability of intermediate *** completes the conversion from power trace to intermediate values and greatly improves the efficiency of the power attack.

关键词： side-channel analysis template attack machine learning deep learning

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：