发布求助
文献互助 智能选刊 最新文献

Proceedings of the 2020 International Conference on Pattern Recognition and Intelligent Systems最新文献

筛选
英文 中文
A Research on the Architecture of Coherent Detection and Its Digital Baseband Algorithms 相干检测体系及其数字基带算法研究
Proceedings of the 2020 International Conference on Pattern Recognition and Intelligent Systems Pub Date : 2020-07-30 DOI: 10.1145/3415048.3416107
Jing Wu
{"title":"A Research on the Architecture of Coherent Detection and Its Digital Baseband Algorithms","authors":"Jing Wu","doi":"10.1145/3415048.3416107","DOIUrl":"https://doi.org/10.1145/3415048.3416107","url":null,"abstract":"With the continuous growth of communication traffic, people's requirements for transmission capacity and transmission rate are increasing. How to realize low-cost and high-speed optical transmission has become an important issue of optical communication technology. Optical transmission system is mainly divided into two types, direct detection transmission system and coherent detection transmission system. Although the cost of direct detection transmission system is comparatively low, the spectrum efficiency is limited. Coherent detection can improve the efficiency of optical transmission. Also, it can greatly improve the system sensitivity and transmission capacity. There are three baseband algorithms in coherent optical communication system, which are orthogonal frequency division multiplexing (OFDM), single carrier frequency domain equalization (SCFDE) and single-carrier frequency division multiple (SCFDM). In this paper, we discuss the architecture of coherent optical communication. In addition, the digital baseband algorithms and electrical transceivers of OFDM, SCFDE and SCFDM are investigated in detail.","PeriodicalId":122511,"journal":{"name":"Proceedings of the 2020 International Conference on Pattern Recognition and Intelligent Systems","volume":"520 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116205981","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
Feature's Selection-Based Shape Complexity for Writer Identification Task 基于选择的特征形状复杂度的写作者识别
Proceedings of the 2020 International Conference on Pattern Recognition and Intelligent Systems Pub Date : 2020-07-30 DOI: 10.1145/3415048.3416102
A. Bensefia, Chawki Djeddi
{"title":"Feature's Selection-Based Shape Complexity for Writer Identification Task","authors":"A. Bensefia, Chawki Djeddi","doi":"10.1145/3415048.3416102","DOIUrl":"https://doi.org/10.1145/3415048.3416102","url":null,"abstract":"Writer Identification task has attracted a lot of research interests due to its wide variety of applications. Different approaches based on various features exist in the literature. However, all these approaches use all the information available in the handwritten sample to identify the writer (relevant or irrelevant). In this paper, we propose an original approach based on a double feature selection process, where the features are represented by graphemes resulting from a segmentation process. These features are analyzed based on their shape complexity, using the Fourier Elliptic transform, and the complexity score is assigned to each grapheme (FECS). The second phase of feature selection is to eliminate the redundancy among the resulting using a sequential clustering algorithm. Two similarity measures are proposed to evaluate the proposed system on 100 writers of the IAM dataset. We obtained a good identification rate of 96% using only 25 graphemes, which is equivalent to 3--4 words.","PeriodicalId":122511,"journal":{"name":"Proceedings of the 2020 International Conference on Pattern Recognition and Intelligent Systems","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115048401","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: 1
Person Authentication with BehavioSense using Keystroke Biometrics 使用击键生物识别技术的行为感知人员认证
Proceedings of the 2020 International Conference on Pattern Recognition and Intelligent Systems Pub Date : 2020-07-30 DOI: 10.1145/3415048.3416118
Marina Zamsheva, Ingo Deutschmann, David Julitz, A. Bienert
{"title":"Person Authentication with BehavioSense using Keystroke Biometrics","authors":"Marina Zamsheva, Ingo Deutschmann, David Julitz, A. Bienert","doi":"10.1145/3415048.3416118","DOIUrl":"https://doi.org/10.1145/3415048.3416118","url":null,"abstract":"This paper presents some results of user authentication using BehavioSec software (BehavioSense). BehavioSense provides continuous authentication using behavioral biometrics. Two different public available databases were used in this work. The databases have different numbers of training, test sets and data structure, so the experiments were carried out with different application scenarios. The best result for one of the databases in this study has the EER value only 2.38%.","PeriodicalId":122511,"journal":{"name":"Proceedings of the 2020 International Conference on Pattern Recognition and Intelligent Systems","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121348084","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: 2
A Statistical Defense Approach for Detecting Adversarial Examples 一种检测对抗性示例的统计防御方法
Proceedings of the 2020 International Conference on Pattern Recognition and Intelligent Systems Pub Date : 2019-08-26 DOI: 10.1145/3415048.3416103
Alessandro Cennamo, Ido Freeman, A. Kummert
{"title":"A Statistical Defense Approach for Detecting Adversarial Examples","authors":"Alessandro Cennamo, Ido Freeman, A. Kummert","doi":"10.1145/3415048.3416103","DOIUrl":"https://doi.org/10.1145/3415048.3416103","url":null,"abstract":"Adversarial examples are maliciously modified inputs created to fool Machine Learning algorithms (ML). The existence of such inputs presents a major issue to the expansion of ML-based solutions. Many researchers have already contributed to the topic, providing both cutting edge-attack techniques and various defense strategies. This work focuses on the development of a system capable of detecting adversarial samples by exploiting statistical information from the training-set. Our detector computes several distorted replicas of the test input, then collects the classifier's prediction vectors to build a meaningful signature for the detection task. Then, the signature is projected onto a class-specific statistic vector to infer the input's nature. The class predicted for the original input is used to select the class-statistic vector. We show that our method reliably detects malicious inputs, outperforming state-of-the-art approaches in various settings, while being complementary to other defense solutions.","PeriodicalId":122511,"journal":{"name":"Proceedings of the 2020 International Conference on Pattern Recognition and Intelligent Systems","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127822540","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: 3
首页 上一页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信