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A CNN-Based Multi-Scale Pooling Strategy for Acoustic Scene Classification 基于 CNN 的声学场景分类多尺度池化策略
IF 0.7 4区 计算机科学 Q3 Engineering Pub Date : 2024-01-01 DOI: 10.1587/transinf.2023edl8048
Rong Huang, Yue Xie
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引用次数: 0
A Coded Aperture as a Key for Information Hiding Designed by Physics-in-the-Loop Optimization 通过环中物理优化设计的编码光圈作为信息隐藏的密钥
IF 0.7 4区 计算机科学 Q3 Engineering Pub Date : 2024-01-01 DOI: 10.1587/transinf.2023mup0003
Tomoki Minamata, Hiroki Hamasaki, Hiroshi Kawasaki, H. Nagahara, Satoshi Ono
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引用次数: 0
Testing and Delay-Monitoring for the High Reliability of Memory-Based Programmable Logic Device 测试和延迟监控,实现基于存储器的可编程逻辑器件的高可靠性
IF 0.7 4区 计算机科学 Q3 Engineering Pub Date : 2024-01-01 DOI: 10.1587/transinf.2023edp7101
Xihong Zhou, Senling Wang, Y. Higami, Hiroshi Takahashi
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引用次数: 0
Speech Rhythm-Based Speaker Embeddings Extraction from Phonemes and Phoneme Duration for Multi-Speaker Speech Synthesis 从音素和音素时长中提取基于语音节奏的说话者嵌入,用于多说话者语音合成
IF 0.7 4区 计算机科学 Q3 Engineering Pub Date : 2024-01-01 DOI: 10.1587/transinf.2023edp7039
Kenichi Fujita, Atsushi Ando, Yusuke Ijima
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引用次数: 0
CQTXNet: A Modified Xception Network with Attention Modules for Cover Song Identification CQTXNet:带有注意力模块的改进型 Xception 网络:用于识别翻唱歌曲
IF 0.7 4区 计算机科学 Q3 Engineering Pub Date : 2024-01-01 DOI: 10.1587/transinf.2023mul0003
Jinsoo Seo, Junghyun Kim, Hyemi Kim
{"title":"CQTXNet: A Modified Xception Network with Attention Modules for Cover Song Identification","authors":"Jinsoo Seo, Junghyun Kim, Hyemi Kim","doi":"10.1587/transinf.2023mul0003","DOIUrl":"https://doi.org/10.1587/transinf.2023mul0003","url":null,"abstract":"","PeriodicalId":55002,"journal":{"name":"IEICE Transactions on Information and Systems","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139128549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Inference Discrepancy Based Curriculum Learning for Neural Machine Translation 基于推理差异的神经机器翻译课程学习
IF 0.7 4区 计算机科学 Q3 Engineering Pub Date : 2024-01-01 DOI: 10.1587/transinf.2023edp7048
Lei Zhou, Ryohei Sasano, Koichi Takeda
{"title":"Inference Discrepancy Based Curriculum Learning for Neural Machine Translation","authors":"Lei Zhou, Ryohei Sasano, Koichi Takeda","doi":"10.1587/transinf.2023edp7048","DOIUrl":"https://doi.org/10.1587/transinf.2023edp7048","url":null,"abstract":"","PeriodicalId":55002,"journal":{"name":"IEICE Transactions on Information and Systems","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139129809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A DFT and IWT-DCT Based Image Watermarking Scheme for Industry 一种基于DFT和IWT-DCT的工业图像水印方案
4区 计算机科学 Q3 Engineering Pub Date : 2023-11-01 DOI: 10.1587/transinf.2022edl8108
Lei LI, Hong-Jun ZHANG, Hang-Yu FAN, Zhe-Ming LU
Until today, digital image watermarking has not been large-scale used in the industry. The first reason is that the watermarking efficiency is low and the real-time performance cannot be satisfied. The second reason is that the watermarking scheme cannot cope with various attacks. To solve above problems, this paper presents a multi-domain based digital image watermarking scheme, where a fast DFT (Discrete Fourier Transform) based watermarking method is proposed for synchronization correction and an IWT-DCT (Integer Wavelet Transform-Discrete Cosine Transform) based watermarking method is proposed for information embedding. The proposed scheme has high efficiency during embedding and extraction. Compared with five existing schemes, the robustness of our scheme is very strong and our scheme can cope with many common attacks and compound attacks, and thus can be used in wide application scenarios.
直到今天,数字图像水印还没有在工业上大规模应用。首先是水印效率低,实时性不能满足要求。第二个原因是水印方案无法应对各种攻击。针对上述问题,本文提出了一种基于多域的数字图像水印方案,提出了一种基于快速离散傅立叶变换(DFT)的同步校正水印方法和基于整数小波变换-离散余弦变换(iwt)的信息嵌入水印方法。该方案具有较高的嵌入和提取效率。与现有的五种方案相比,该方案具有很强的鲁棒性,能够应对多种常见攻击和复合攻击,具有广泛的应用前景。
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引用次数: 0
Unsupervised Techniques for Identifying the Mode of a Multi-Functional Radar with Varying Pulse Sequences 变脉冲序列多功能雷达模式识别的无监督技术
4区 计算机科学 Q3 Engineering Pub Date : 2023-11-01 DOI: 10.1587/transinf.2023edp7007
Jayson ROOK, Chi-Hao CHENG
A multifunctional radar (MFR) with varying pulse sequences can change its signal characteristics and/or pattern, based on the presence of targets and to avoid being jammed. To take a countermeasure against an MFR, it is crucial for an electronic warfare (EW) system to be able to identify and separate a MFR's modes via analyzing intercepted radar signals, without a priori knowledge. In this article, two correlation-based methods, one taking the signal's order into account and another one ignoring the signal's order, are proposed and investigated for this task. The results demonstrate their great potential.
具有不同脉冲序列的多功能雷达(MFR)可以根据目标的存在改变其信号特性和/或模式,以避免被阻塞。为了采取对抗MFR的对策,电子战(EW)系统能够在没有先验知识的情况下,通过分析截获的雷达信号来识别和分离MFR的模式,这是至关重要的。在本文中,提出并研究了两种基于相关的方法,一种是考虑信号的顺序,另一种是忽略信号的顺序。结果显示了它们的巨大潜力。
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引用次数: 0
Kiite Cafe: A Web Service Enabling Users to Listen to the Same Song at the Same Moment While Reacting to the Song Kiite Cafe:一种网络服务,允许用户在同一时刻听同一首歌,同时对这首歌做出反应
4区 计算机科学 Q3 Engineering Pub Date : 2023-11-01 DOI: 10.1587/transinf.2023edp7001
Kosetsu TSUKUDA, Keisuke ISHIDA, Masahiro HAMASAKI, Masataka GOTO
This paper describes a public web service called Kiite Cafe that lets users get together virtually to listen to music. When users listen to music on Kiite Cafe, their experiences are enhanced by two architectures: (i) visualization of each user's reactions, and (ii) selection of songs from users' favorite songs. These architectures enable users to feel social connection with others and the joy of introducing others to their favorite songs as if they were together listening to music in person. In addition, the architectures provide three user experiences: (1) motivation to react to played songs, (2) the opportunity to listen to a diverse range of songs, and (3) the opportunity to contribute as a curator. By analyzing the behavior logs of 2,399 Kiite Cafe users over a year, we quantitatively show that these user experiences can generate various effects (e.g., users react to a more diverse range of songs on Kiite Cafe than when listening alone). We also discuss how our proposed architectures can enrich music listening experiences with others.
本文描述了一个名为Kiite Cafe的公共网络服务,它可以让用户虚拟地聚在一起听音乐。当用户在Kiite Cafe听音乐时,他们的体验通过两个架构得到增强:(i)每个用户反应的可视化,以及(ii)从用户最喜欢的歌曲中选择歌曲。这些架构使用户能够感受到与他人的社交联系,以及向他人介绍自己喜欢的歌曲的乐趣,就像他们在一起亲自听音乐一样。此外,这些架构还提供了三种用户体验:(1)对播放的歌曲做出反应的动机,(2)听各种各样歌曲的机会,以及(3)作为策展人做出贡献的机会。通过分析2399名Kiite Cafe用户在一年内的行为日志,我们定量地表明,这些用户体验可以产生各种各样的效果(例如,用户对Kiite Cafe上的各种歌曲的反应比单独听音乐时更多样化)。我们还讨论了我们提出的架构如何与他人一起丰富音乐聆听体验。
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引用次数: 0
Implementing Region-Based Segmentation for Hardware Trojan Detection in FPGAs Cell-Level Netlist 基于区域分割的fpga单元级网表硬件木马检测
4区 计算机科学 Q3 Engineering Pub Date : 2023-11-01 DOI: 10.1587/transinf.2023edl8036
Ann Jelyn TIEMPO, Yong-Jin JEONG
Field Programmable Gate Array (FPGA) is gaining popularity because of their reconfigurability which brings in security concerns like inserting hardware trojan. Various detection methods to overcome this threat have been proposed but in the ASIC's supply chain and cannot directly apply to the FPGA application. In this paper, the authors aim to implement a structural feature-based detection method for detecting hardware trojan in a cell-level netlist, which is not well explored yet, where the nets are segmented into smaller groups based on their interconnection and further analyzed by looking at their structural similarities. Experiments show positive performance with an average detection rate of 95.41%, an average false alarm rate of 2.87% and average accuracy of 96.27%.
现场可编程门阵列(FPGA)由于其可重构性而越来越受欢迎,但同时也带来了硬件木马等安全问题。已经提出了各种检测方法来克服这种威胁,但在ASIC的供应链中,不能直接应用于FPGA应用。在本文中,作者的目标是实现一种基于结构特征的检测方法,用于检测细胞级网络列表中的硬件木马,该方法尚未得到很好的探索,其中网络根据其互连被分割成更小的组,并通过查看其结构相似性进一步分析。实验结果表明,该算法的平均检测率为95.41%,平均虚警率为2.87%,平均准确率为96.27%。
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引用次数: 0
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IEICE Transactions on Information and Systems
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