International Conference on Algorithms, Microchips and Network Applications最新文献

An efficient 3D point cloud classification approach via persistent homology 通过持久同源性实现高效的 3D 点云分类方法

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2024-06-08 DOI: 10.1117/12.3032040

Xin-Yu Zhou, Yu Pan, Lei Zhang, Huafei Sun*

引用次数: 0

Research on offloading strategies for mobile edge computing in ultradense networks 超密集网络中移动边缘计算的卸载策略研究

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2024-06-08 DOI: 10.1117/12.3032060

Ruobin Wang, Lijun Li, Meiling Li, Wenhua Gao, Zengshou Dong

引用次数: 0

Towards recognition of open-set speech forgery algorithms by using prototype learning 利用原型学习识别开放集语音伪造算法

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2024-06-08 DOI: 10.1117/12.3031938

Zuxing Zhao, Haiyan Zhang, Hai Min, Yanxiang Chen

{"title":"Towards recognition of open-set speech forgery algorithms by using prototype learning","authors":"Zuxing Zhao, Haiyan Zhang, Hai Min, Yanxiang Chen","doi":"10.1117/12.3031938","DOIUrl":"https://doi.org/10.1117/12.3031938","url":null,"abstract":"Recent advances in machine learning have made forged video and audio more convincing. This poses a threat to the security of individuals, societies and nations. To address this threat, the ASVspoof initiative was conceived to spearhead research on Automatic Speaker Verification (ASV) for anti-spoofing. Currently, most research on ASVspoof has focused on detecting whether speech has been tampered with. However, little attention has been paid to the recognition of speech forgery algorithms. Moreover, in the real world, new forgery algorithms keep emerging, making it difficult to adapt forgery algorithm recognition models trained under closed-set conditions to realistic open-set scenarios. Therefore, we propose a method based on prototype learning and adaptive thresholding for recognizing speech forgery algorithms in open-set. The method uses manifold mixup and dummy prototypes to simulate and recognize unknown speech forgery algorithms. Prototype classification improves the ability to recognize speech forgery algorithms with high similarity. At the same time, it has the advantage of preventing catastrophic forgetting and facilitates subsequent incremental training using samples of newly recognized forgery algorithms. Thus, our method increases the number of recognized categories for forgery algorithms. Experimental results show that our method is effective. The codes are available at https://github.com/multimedia-security/open-set-recognization.","PeriodicalId":342847,"journal":{"name":"International Conference on Algorithms, Microchips and Network Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141369856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DOA estimation based on mode and maximum eigenvector algorithm with reverberation environment 基于混响环境下模式和最大特征向量算法的 DOA 估计

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2024-06-08 DOI: 10.1117/12.3032086

Hengyi Liu, Zhenghong Liu, Linxia Su, Liyan Luo

引用次数: 0

Network communication optimization of RCCL communication library in Multi-NIC systems 多网卡系统中 RCCL 通信库的网络通信优化

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2024-06-08 DOI: 10.1117/12.3031956

Shuaiming He, Wei Wan, Junhong Li

{"title":"Network communication optimization of RCCL communication library in Multi-NIC systems","authors":"Shuaiming He, Wei Wan, Junhong Li","doi":"10.1117/12.3031956","DOIUrl":"https://doi.org/10.1117/12.3031956","url":null,"abstract":"With the widespread application of deep learning frameworks, large-scale computing and GPU programming are receiving increased attention. For upper-layer applications that utilize GPUs for computational communication, such as TensorFlow and PyTorch, improving the communication efficiency of the underlying communication library is of paramount importance to enhance the overall performance of the frameworks. Among them, the RCCL (Rocm Collective Communication Library) GPU communication library, provided by the Rocm (Radeon Open Compute platform) computing platform, supports various collective communication operations and point-to-point operations. Through analysis, we have identified a problem in the initialization and usage of the ring channel network in the RCCL library, specifically in multi-network card systems. This issue results in certain network cards being unable to communicate, leading to wasted system resources. To address this problem, optimizations can be made at the code level by introducing data structures and algorithms to control the invocation of network cards. The goal is to adjust the usage strategy of multiple network cards in the ring channel network without modifying the original design concept of RCCL. After optimization, extensive evaluations were conducted using a large-scale GPU cluster. The optimized RCCL library achieved significant improvements in communication performance. Under a communication scale of 16 compute nodes and 64 GPUs, the peak bandwidth increased from 5.28GB/s to 7.78GB/s. In inter-node collective communication tests, the performance improvement reached up to 60%. The improved RCCL library provides better low-level communication performance for upper-layer applications on the Rocm computing platform, offering enhanced communication support.","PeriodicalId":342847,"journal":{"name":"International Conference on Algorithms, Microchips and Network Applications","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141369647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A directional MAC protocol for marine ship ad-hoc networks 适用于海洋舰船 ad-hoc 网络的定向 MAC 协议

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2024-06-08 DOI: 10.1117/12.3032021

Xiaoran Yang, Shengming Jiang

引用次数: 0

Multi-UAV tracking target in urban environments by model predictive control and improved whale optimizer 利用模型预测控制和改进的鲸鱼优化器在城市环境中追踪多无人机目标

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2024-06-08 DOI: 10.1117/12.3032000

Yongheng Zhao, Xuzhao Chai, Cuicui He, Yiming Lu, Pengwei Wen, Li Yan, Zhao Li

引用次数: 0

A lightweight car damage detection algorithm 轻量级汽车损坏检测算法

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2024-06-08 DOI: 10.1117/12.3031904

Qishan Pei, Xinkuang Wang, Zhongcheng Wu

引用次数: 0

High-efficiency silicon modulator of horizontal S-shaped profile 水平 S 型高效硅调制器

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2024-06-08 DOI: 10.1117/12.3031892

Zijian Zhu, Ying Zhao, Fuwan Gan

引用次数: 0

Image denoising algorithm based on self-attention residual network 基于自注意残差网络的图像去噪算法

International Conference on Algorithms, Microchips and Network Applications Pub Date : 2024-06-08 DOI: 10.1117/12.3031897

Wei Wu, Hao Wu

引用次数: 0