標題: Titlebook: Handbook of Biometric Anti-Spoofing; Presentation Attack Sébastien Marcel,Julian Fierrez,Nicholas Evans Book 2023Latest edition The Editor [打印本頁] 作者: endocarditis 時間: 2025-3-21 18:59
書目名稱Handbook of Biometric Anti-Spoofing影響因子(影響力)
書目名稱Handbook of Biometric Anti-Spoofing影響因子(影響力)學科排名
書目名稱Handbook of Biometric Anti-Spoofing網(wǎng)絡(luò)公開度
書目名稱Handbook of Biometric Anti-Spoofing網(wǎng)絡(luò)公開度學科排名
書目名稱Handbook of Biometric Anti-Spoofing被引頻次
書目名稱Handbook of Biometric Anti-Spoofing被引頻次學科排名
書目名稱Handbook of Biometric Anti-Spoofing年度引用
書目名稱Handbook of Biometric Anti-Spoofing年度引用學科排名
書目名稱Handbook of Biometric Anti-Spoofing讀者反饋
書目名稱Handbook of Biometric Anti-Spoofing讀者反饋學科排名
作者: 貪婪的人 時間: 2025-3-21 22:23 作者: ALLEY 時間: 2025-3-22 02:44
https://doi.org/10.1007/978-1-4612-1672-8 this study, we reformulate the workings of a typical fingerprint recognition system. We show that both spoof detection and fingerprint recognition are correlated tasks, and therefore, rather than performing these two tasks separately, a joint model capable of performing both spoof detection and mat作者: Nonthreatening 時間: 2025-3-22 06:40
Maciej Stolarski,Joanna Witowska to real-world applications. The deployment of this technology raises questions about the main vulnerabilities and security threats related to these systems. Among these threats, presentation attacks stand out as some of the most relevant and studied. Presentation attacks can be defined as the prese作者: FIS 時間: 2025-3-22 08:51
Antanas Kairys,Audrone Liniauskaite used in iris recognition systems. A pupil, when stimulated by visible light in a predefined manner, may offer sophisticated dynamic liveness features that cannot be acquired from dead eyes or other static objects such as printed contact lenses, paper printouts, or prosthetic eyes. Modeling of pupil作者: 招募 時間: 2025-3-22 12:55 作者: 入伍儀式 時間: 2025-3-22 17:51 作者: legislate 時間: 2025-3-22 21:18
https://doi.org/10.1007/978-3-662-53430-4 in the last few years. The next pages present the different presentation attacks that a face recognition system can confront, in which an attacker presents to the sensor, mainly a camera, a Presentation Attack Instrument (PAI), that is generally a photograph, a video, or a mask, with the target to 作者: 得罪人 時間: 2025-3-23 05:03
State Estimation in the State-Space Model,which brings a big challenge to face presentation attack detection (PAD). With the boosting of face recognition application in wide scenarios, there is an urgent need to solve the 3D facial mask attack problem. Since this appearance and material of 3D masks could vary in a much larger range compared作者: Salivary-Gland 時間: 2025-3-23 06:20 作者: Misgiving 時間: 2025-3-23 11:48 作者: Hyperalgesia 時間: 2025-3-23 16:29 作者: HAVOC 時間: 2025-3-23 18:33
Time Use Research in the Social Sciences to a binary classification problem. In this article, by analyzing distributions of genuine and replayed speech with a specifically designed database and summarizing the known artifacts in existing datasets, we show the potential shortcomings of the two-class approach in both discrimination and gene作者: SHRIK 時間: 2025-3-23 22:57 作者: faction 時間: 2025-3-24 02:43
Vision Transformers for Fingerprint Presentation Attack Detectionof presentation attack species (i.e., artifacts), varying from low-cost artifacts to sophisticated materials. A number of presentation attack detection (PAD) approaches have been specifically designed to detect and counteract presentation attacks on fingerprint systems. In this chapter, we study and作者: 變色龍 時間: 2025-3-24 10:18
Review of the Fingerprint Liveness Detection (LivDet) Competition Series: From 2009 to 2021resentation attacks is not trivial because attackers refine their replication techniques from year to year. The International Fingerprint liveness Detection Competition (LivDet), an open and well-acknowledged meeting point of academies and private companies that deal with the problem of presentation作者: 大量 時間: 2025-3-24 13:40 作者: Bernstein-test 時間: 2025-3-24 18:31 作者: GROVE 時間: 2025-3-24 22:34 作者: TAG 時間: 2025-3-25 01:25
Review of Iris Presentation Attack Detection Competitionsic sample from a genuine user. Presentation Attack Detection (PAD) is suggested as a solution to this vulnerability. The LivDet-Iris Liveness Detection Competition strives to showcase the state of the art in presentation attack detection by assessing the software-based iris Presentation Attack Detec作者: 馬具 時間: 2025-3-25 06:43 作者: intercede 時間: 2025-3-25 10:14
Introduction to Presentation Attack Detection in Face Biometrics and Recent Advances in the last few years. The next pages present the different presentation attacks that a face recognition system can confront, in which an attacker presents to the sensor, mainly a camera, a Presentation Attack Instrument (PAI), that is generally a photograph, a video, or a mask, with the target to 作者: 無瑕疵 時間: 2025-3-25 13:59 作者: 東西 時間: 2025-3-25 16:36
Robust Face Presentation Attack Detection with Multi-channel Neural Networksave been proposed in the literature for the detection of presentation attacks, majority of these methods fail in generalizing to unseen attacks and environments. Since the quality of attack instruments keeps getting better, the difference between bona fide and attack samples is diminishing making it作者: Prophylaxis 時間: 2025-3-25 22:30
Review of Face Presentation Attack Detection Competitions state of the art in unimodal and multi-modal face anti-spoofing has been assessed in eight international competitions organized in conjunction with major biometrics and computer vision conferences in 2011, 2013, 2017, 2019, 2020 and 2021, each introducing new challenges to the research community. I作者: 深淵 時間: 2025-3-26 02:54 作者: 雜役 時間: 2025-3-26 06:34
A One-class Model for Voice Replay Attack Detection to a binary classification problem. In this article, by analyzing distributions of genuine and replayed speech with a specifically designed database and summarizing the known artifacts in existing datasets, we show the potential shortcomings of the two-class approach in both discrimination and gene作者: 招致 時間: 2025-3-26 12:18
Generalizing Voice Presentation Attack Detection to?Unseen Synthetic Attacks and?Channel Variation, text-to-speech (TTS), and voice conversion (VC) techniques, which may compromise ASV systems. Voice presentation attack detection (PAD) is developed to improve the reliability of speaker verification systems against such spoofing attacks. One main issue of voice PAD systems is its generalization a作者: HACK 時間: 2025-3-26 14:08
Time Domain Representation of Speech Soundschapter covers both spectrum of CNNs and vision transformers to provide the reader with a one-place reference for understanding the performance of various architectures. Vision transformers provide at par results for the fingerprint PAD compared to CNNs with more extensive training duration suggesti作者: 講個故事逗他 時間: 2025-3-26 20:14
Maciej Stolarski,Joanna Witowskaacks. First, we summarize the most popular types of attacks including the main challenges to address. Second, we present a taxonomy of PAD methods as a brief introduction to this very active research area. Finally, we discuss the integration of these methods into iris recognition systems according t作者: Monolithic 時間: 2025-3-26 21:09
Antanas Kairys,Audrone Liniauskaiteurrent neural networks and compares their PAD performance to solutions based on the parametric Clynes-Kohn model and various classification techniques. Experiments with 166 distinct eyes of 84 subjects show that the best data-driven solution, one based on long short-term memory, was able to correctl作者: 洞察力 時間: 2025-3-27 04:39
Time Pressure in Negotiation and Mediation the other two happening in 2015 and 2017. This chapter briefly characterizes all four competitions, discusses the state of the art in iris PAD (from the independent evaluations point of view), and current needs to push the iris PAD reliability forward.作者: fallible 時間: 2025-3-27 08:10
Time-Reversal Acoustics and Superresolution,ormed on six NIR and one visible-light iris databases to show the effectiveness and robustness of proposed A-PBS methods. We additionally conduct extensive experiments under intra-/cross-database and intra-/cross-spectrum for detailed analysis. The results of our experiments indicate the generalizab作者: 裂隙 時間: 2025-3-27 12:52 作者: scoliosis 時間: 2025-3-27 15:12
https://doi.org/10.1007/978-3-030-46347-2 Specifically, we present different architecture choices for fusion, along with ad hoc loss functions as opposed to standard classification objective. We conduct an extensive set of experiments in the HQ-WMCA dataset, which contains a wide variety of attacks and sensing channels together with challe作者: Exterior 時間: 2025-3-27 19:59 作者: JOT 時間: 2025-3-27 23:40
2191-6586 eviewof competition series; examines methods for PAD in iris recognition systems, the use of pupil size measurement or multiple spectra for this purpose; discusses advancements in PAD methods for face recogniti978-981-19-5290-6978-981-19-5288-3Series ISSN 2191-6586 Series E-ISSN 2191-6594 作者: duplicate 時間: 2025-3-28 02:50 作者: CRP743 時間: 2025-3-28 06:23
Introduction to Presentation Attack Detection in Iris Biometrics and Recent Advancesacks. First, we summarize the most popular types of attacks including the main challenges to address. Second, we present a taxonomy of PAD methods as a brief introduction to this very active research area. Finally, we discuss the integration of these methods into iris recognition systems according t作者: GUILT 時間: 2025-3-28 13:22 作者: 擋泥板 時間: 2025-3-28 17:59 作者: 得體 時間: 2025-3-28 22:29 作者: Corroborate 時間: 2025-3-28 23:16 作者: 懶鬼才會衰弱 時間: 2025-3-29 03:08
Robust Face Presentation Attack Detection with Multi-channel Neural Networks Specifically, we present different architecture choices for fusion, along with ad hoc loss functions as opposed to standard classification objective. We conduct an extensive set of experiments in the HQ-WMCA dataset, which contains a wide variety of attacks and sensing channels together with challe作者: Sinus-Rhythm 時間: 2025-3-29 08:11
Generalizing Voice Presentation Attack Detection to?Unseen Synthetic Attacks and?Channel Variationel-robust training strategies, including data augmentation, multi-task learning, and adversarial learning. In this chapter, we analyze the two issues within the scope of synthetic attacks, i.e., TTS and VC, and demonstrate the effectiveness of our proposed methods.作者: labyrinth 時間: 2025-3-29 12:15 作者: 補角 時間: 2025-3-29 17:50 作者: 驚惶 時間: 2025-3-29 22:52 作者: 少量 時間: 2025-3-30 00:24
Time Shaping for Business Successtest three competitions focused on evaluating domain and attack type generalization abilities of face PAD algorithms operating on conventional colour images and videos. We also discuss the lessons learnt from the competitions and future challenges in the field in general.作者: OMIT 時間: 2025-3-30 05:03 作者: strain 時間: 2025-3-30 11:06 作者: 得罪 時間: 2025-3-30 13:43
Review of Face Presentation Attack Detection Competitionstest three competitions focused on evaluating domain and attack type generalization abilities of face PAD algorithms operating on conventional colour images and videos. We also discuss the lessons learnt from the competitions and future challenges in the field in general.作者: rectum 時間: 2025-3-30 19:16 作者: AUGER 時間: 2025-3-30 21:27 作者: 嫻熟 時間: 2025-3-31 03:21
