作者: Adjourn 時(shí)間: 2025-3-21 21:56 作者: Kaleidoscope 時(shí)間: 2025-3-22 01:24 作者: adjacent 時(shí)間: 2025-3-22 06:39 作者: Root494 時(shí)間: 2025-3-22 10:36
MultiBioGM: A Hand Multimodal Biometric Model Combining Texture Prior Knowledge to?Enhance Generalizralization model MultiBioGM. Experimental results on three multimodal datasets demonstrate the effectiveness of our model for biometrics, which achieves 0.098%, 0.024%, and 0.117% EERs on unobserved data.作者: STEER 時(shí)間: 2025-3-22 15:20 作者: Psychogenic 時(shí)間: 2025-3-22 17:07
Facial Adversarial Sample Augmentation for?Robust Low-Quality 3D Face Recognitionodule, a distribution alignment loss is designed to make the distribution of facial adversarial samples gradually close to the one of the original facial samples, and the common and valuable information from both distributions can be effectively extracted. Extensive experiments conducted on the CAS-作者: Melodrama 時(shí)間: 2025-3-22 22:10 作者: 幻影 時(shí)間: 2025-3-23 03:09
More on Generalized Derivatives, palmprint images. Lastly, we reconstruct the super-resolution palmprint images with clear palmprint-specific texture and edge characteristics via two convolutional layers with embedding a PixelShuffle. Experimental results on three public palmprint databases clearly show the effectiveness of the pr作者: 上腭 時(shí)間: 2025-3-23 08:09 作者: 拋射物 時(shí)間: 2025-3-23 13:30 作者: Left-Atrium 時(shí)間: 2025-3-23 17:49 作者: accessory 時(shí)間: 2025-3-23 18:14
Fluid Construction Grammar on Real Robotsralization model MultiBioGM. Experimental results on three multimodal datasets demonstrate the effectiveness of our model for biometrics, which achieves 0.098%, 0.024%, and 0.117% EERs on unobserved data.作者: 使人入神 時(shí)間: 2025-3-24 01:25
Lecture Notes in Computer Sciencerating these multi-dimensional feature nets, our proposed integrated network can extract the robust and complementary age features between RGB and depth modalities. Extensive experimental results on the widely used databases clearly demonstrate the effectiveness of our proposed method.作者: glacial 時(shí)間: 2025-3-24 04:05 作者: 天氣 時(shí)間: 2025-3-24 10:30
Patrick Stevenson,Clare Mar-Molineroed on AptG that models the relationships within the affective labels. Moreover, we propose a parallel superposition mechanism to obtain a richer information representation. Experiments on the wild datasets AffectNet and Aff-Wild2 validate the effectiveness of our method. The results of public benchm作者: 叢林 時(shí)間: 2025-3-24 12:41
Unsupervised Fingerprint Dense Registrationistration methods need sufficient amount of labeled fingerprint pairs which are difficult to obtain. In addition, the training data itself may not include enough variety of fingerprints thus limit such methods’ performance. In this work, we propose an unsupervised end-to-end framework for fingerprin作者: 石墨 時(shí)間: 2025-3-24 18:53 作者: 敬禮 時(shí)間: 2025-3-24 21:38
U-PISRNet: A Unet-Shape Palmprint Image Super-Resolution Networkmprint recognition methods focus only feature representation and matching under an assumption that palmprint images are high-quality, while practical palmprint images are usually captured by various cameras under diverse backgrounds, heavily reducing the quality of palmprint images. To address this,作者: Optometrist 時(shí)間: 2025-3-25 01:21 作者: 水土 時(shí)間: 2025-3-25 05:58
A Comparative Study on?Canonical Correlation Analysis-Based Multi-feature Fusion for?Palmprint Recogly, many existing methods have shown relatively satisfying performance, but there are still several problems such as the limited patterns extracted by single feature extraction approach and the huge gap between hand-crafted feature-based approaches and deep learning feature-based approaches. To this作者: 珠寶 時(shí)間: 2025-3-25 09:37 作者: Indict 時(shí)間: 2025-3-25 13:47 作者: somnambulism 時(shí)間: 2025-3-25 16:16 作者: Fissure 時(shí)間: 2025-3-25 20:22
Cross-Sensor Fingerprint Recognition Based on Style Transfer Network and Score Fusionsystemic deformation and the different imaging style. Most of the existing fingerprint recognition methods fail to consider the problem of cross-sensor fingerprint verification. This paper proposes a cross-sensor fingerprint recognition system based on style transfer and score fusion. The method use作者: 吃掉 時(shí)間: 2025-3-26 01:48
Sparse Coding of?Deep Residual Descriptors for?Vein Recognitionunderlying issues such as uneven illumination, low contrast, and sparse patterns with high inter-class similarities make the traditional vein recognition systems based on hand-engineered features unreliable. To address the difficulty of direct training or fine-tuning a CNN with existing small-scale 作者: Heresy 時(shí)間: 2025-3-26 05:57
MultiBioGM: A Hand Multimodal Biometric Model Combining Texture Prior Knowledge to?Enhance Generaliztional machine learning or deep learning have been proposed. However, the generalization ability of these methods is not satisfying due to the different entities, backgrounds, and sensors. In this paper, based on the three modalities of fingerprint, fingervein, and palmprint, the texture prior knowl作者: Flavouring 時(shí)間: 2025-3-26 11:27
RRFAE-Net: Robust RGB-D Facial Age Estimation Networkntity-related representation. However, most existing facial age estimation methods usually extract age features from the RGB images, making them sensitive to the gender, race, pose and illumination changes. In this paper, we propose an end-to-end multi-feature integrated network for robust RGB-D fac作者: Pamphlet 時(shí)間: 2025-3-26 13:30 作者: 有惡臭 時(shí)間: 2025-3-26 19:03 作者: 小爭(zhēng)吵 時(shí)間: 2025-3-26 23:00 作者: 拋棄的貨物 時(shí)間: 2025-3-27 03:25 作者: syring 時(shí)間: 2025-3-27 08:10
Affective Prior Topology Graph Guided Facial Expression Recognitionly concentrated on emotion classification or sentiment levels, disregarding the crucial dependencies between these factors that are vital for perceiving human emotions. To address this problem, we propose a novel affective priori topology graph network (AptGATs). AptGATs explicitly captures the topo作者: VEIL 時(shí)間: 2025-3-27 12:21
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/188172.jpg作者: lattice 時(shí)間: 2025-3-27 17:40
Gilles Barthe,Benjamin Grégoire,Colin Ribaistration methods need sufficient amount of labeled fingerprint pairs which are difficult to obtain. In addition, the training data itself may not include enough variety of fingerprints thus limit such methods’ performance. In this work, we propose an unsupervised end-to-end framework for fingerprin作者: staging 時(shí)間: 2025-3-27 18:34 作者: Overdose 時(shí)間: 2025-3-28 00:00
More on Generalized Derivatives,mprint recognition methods focus only feature representation and matching under an assumption that palmprint images are high-quality, while practical palmprint images are usually captured by various cameras under diverse backgrounds, heavily reducing the quality of palmprint images. To address this,作者: 分發(fā) 時(shí)間: 2025-3-28 05:22 作者: Orgasm 時(shí)間: 2025-3-28 07:05
https://doi.org/10.1057/978-1-137-58746-6ly, many existing methods have shown relatively satisfying performance, but there are still several problems such as the limited patterns extracted by single feature extraction approach and the huge gap between hand-crafted feature-based approaches and deep learning feature-based approaches. To this作者: DEFER 時(shí)間: 2025-3-28 12:44
Open-ended Procedural Semanticscies in finger vein (FV) recognition, there still remain some unresolved issues, including high model complexity and memory cost, as well as insufficient training samples. To address these issues, we propose an unsupervised spiking neural network for finger vein recognition (hereinafter dubbed ‘FV-S作者: 考古學(xué) 時(shí)間: 2025-3-28 17:49
Luc Steels,Joachim De Beule,Pieter Wellensttack performance. However, in practical applications, it is inevitably affected by certain external environments and bring out performance reduction, such as the droplet problem, which is rarely solved in current research works nevertheless. Facing this challenge, this paper proposes a feature-fuse作者: MULTI 時(shí)間: 2025-3-28 20:20
An Experiment in Temporal Language Learning door locks and mobile phone security, to more critical realms like public security and legal identification. However, traditional contact-based fingerprint recognition methods bear the drawbacks of compromising the fingerprint’s intrinsic 3D structure and being susceptible to contamination. In cont作者: 徹底檢查 時(shí)間: 2025-3-29 01:37 作者: Flagging 時(shí)間: 2025-3-29 03:10
Katrien Beuls,Remi van Trijp,Pieter Wellensunderlying issues such as uneven illumination, low contrast, and sparse patterns with high inter-class similarities make the traditional vein recognition systems based on hand-engineered features unreliable. To address the difficulty of direct training or fine-tuning a CNN with existing small-scale 作者: 廢除 時(shí)間: 2025-3-29 09:27
Fluid Construction Grammar on Real Robotstional machine learning or deep learning have been proposed. However, the generalization ability of these methods is not satisfying due to the different entities, backgrounds, and sensors. In this paper, based on the three modalities of fingerprint, fingervein, and palmprint, the texture prior knowl作者: MITE 時(shí)間: 2025-3-29 14:34
Lecture Notes in Computer Sciencentity-related representation. However, most existing facial age estimation methods usually extract age features from the RGB images, making them sensitive to the gender, race, pose and illumination changes. In this paper, we propose an end-to-end multi-feature integrated network for robust RGB-D fac作者: diabetes 時(shí)間: 2025-3-29 18:03
SpringerBriefs in Speech Technologypoint (ICP) require laborious pairwise registration, so in this paper we focus on deep learning methods for human identification using tooth. We propose a complete workflow for tooth segmentation and recognition based on PointNet++?using the 3D intraoral scanning (IOS) model. Our method consists of 作者: expository 時(shí)間: 2025-3-29 23:36 作者: 知識(shí)分子 時(shí)間: 2025-3-30 00:53
https://doi.org/10.1007/978-3-319-17163-0atabase based on queries given as texts, which holds significant potential for practical applications in public security and multimedia. Our approach employs a vision-language pre-training model as the backbone, effectively incorporating contrastive learning, image-text matching learning, and masked作者: 和音 時(shí)間: 2025-3-30 05:30 作者: Atrium 時(shí)間: 2025-3-30 09:30 作者: BOON 時(shí)間: 2025-3-30 14:19
https://doi.org/10.1007/978-981-99-8565-4fingerprint; palmprint; vein recognition; face detection; affective computing and human-computer interfa作者: 萬(wàn)神殿 時(shí)間: 2025-3-30 19:36
978-981-99-8564-7The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor作者: ADORE 時(shí)間: 2025-3-30 21:00 作者: cravat 時(shí)間: 2025-3-31 01:33 作者: deviate 時(shí)間: 2025-3-31 06:49
Conference proceedings 2023print and Vein Recognition; Face Detection, Recognition and Tracking; Affective Computing and Human-Computer Interface; Trustworthy, Privacy and Personal Data Security; Medical and Other Applications.?.作者: 啜泣 時(shí)間: 2025-3-31 13:06
0302-9743 rint, Palmprint and Vein Recognition; Face Detection, Recognition and Tracking; Affective Computing and Human-Computer Interface; Trustworthy, Privacy and Personal Data Security; Medical and Other Applications.?.978-981-99-8564-7978-981-99-8565-4Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: cardiac-arrest 時(shí)間: 2025-3-31 14:01
More on Generalized Derivatives,ion accuracy under various scenarios, including complex backgrounds and special hand shapes. The proposed approach in this paper enables non-contact palm recognition technology, implementing 360-degree omnidirectional recognition, thereby improving convenience and feasibility in its usage.
