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Solving the Federated Edge Learning Participation Dilemma: A Truthful and Correlated Perspective

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arXiv 2022年

作者： Hu, Qin Li, Feng Zou, Xukai Xiao, Yinhao Department of Computer and Information Science Indiana University-Purdue University IndianapolisIN United States Department of Computer Information and Graphics Technology Indiana University-Purdue University IndianapolisIN United States School of Information Science Guangdong University of Finance and Economics Guangzhou China

An emerging computational paradigm, named federated edge learning (FEL), enables intelligent computing at the network edge with the feature of preserving data privacy for edge devices. Given their constrained resources, it becomes a great challenge to achieve high execution performance for FEL. Most of the state-of-the-arts concentrate on enhancing FEL from the perspective of system operation procedures, taking few precautions during the composition step of the FEL system. Though a few recent studies recognize the importance of FEL formation and propose server-centric device selection schemes, the impact of data sizes is largely overlooked. In this paper, we take advantage of game theory to depict the decision dilemma among edge devices regarding whether to participate in FEL or not given their heterogeneous sizes of local datasets. For realizing both the individual and global optimization, the server is employed to solve the participation dilemma, which requires accurate information collection for devices’ local datasets. Hence, we utilize mechanism design to enable truthful information solicitation. With the help of correlated equilibrium, we derive a decision making strategy for devices from the global perspective, which can achieve the long-term stability and efficacy of FEL. For scalability consideration, we optimize the computational complexity of the basic solution to the polynomial level. Lastly, extensive experiments based on both real and synthetic data are conducted to evaluate our proposed mechanisms, with experimental results demonstrating the performance advantages. Copyright © 2022, The Authors. All rights reserved.

关键词： Decision making

Development of software for the implementation of an adaptive approach to the generation of internal filling of a 3D model in additive manufacturing

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Development of software for the implementation of an adaptiv...

2021 International Conference on Automatics and Energy, ICAE 2021

作者： Kholodilov, A.A. Faleeva, E.V. Kholodilova, M.V. Department of "Computer Science and Computer Graphics" Far Eastern State Transport University Serysheva st. 47 Khabarovsk680021 Russia Computing Center The Far Eastern Branch Russian Academy of Sciences Kim Yoo Jong st. 65 Khabarovsk680000 Russia

The article describes the technology of software development for the implementation of an adaptive approach to generating the external and internal structure of a 3D model in preparation for 3D printing when transferring from *.stl format to * *** format. The main stages of software design, the principles of mathematical modeling underlying the development are considered, the practical significance of the developed software complex-slicer is shown with a description of the functionality and conceptual development. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： 3D printers

Investigation of the mathematical and software implementation of triangulation mesh generation algorithms in relation to the creation of a slicer program

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Investigation of the mathematical and software implementatio...

2021 International Conference on Automatics and Energy, ICAE 2021

作者： Kholodilov, A.A. Faleeva, E.V. Kholodilova, M.V. Department of "Computer Science and Computer Graphics" Far Eastern State Transport University st. Serysheva 47 Khabarovsk680021 Russia Computing Center The Far Eastern Branch Russian Academy of Sciences st. Kim Yoo Jong 65 Khabarovsk680000 Russia

The article discusses an algorithmic method for increasing the strength characteristics of products produced by additive manufacturing technologies through thickening the internal grid structure of filling the model when transferring to the control code during the operation of the slicer program. It shows the internal filling using the Voronoi grid and the "Exhaustion Algorithm" for the implementation of the internal filling of the three-dimensional model in the process of the slicer program. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Filling

VibraForge: A Scalable Prototyping Toolkit For Creating Spatialized Vibrotactile Feedback Systems

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arXiv 2024年

作者： Huang, Bingjian Ren, Siyi Luo, Yuewen Cheng, Qilong Cai, Hanfeng Sang, Yeqi Sousa, Mauricio Dietz, Paul H. Wigdor, Daniel Dynamic Graphics Project Lab University of Toronto TorontoON Canada Division of Engineering Science University of Toronto TorontoON Canada University of Toronto TorontoON Canada Department of Electrical and Computer Engineering University of Toronto TorontoON Canada Department of Mechanical & Industrial Engineering University of Toronto TorontoON Canada

Spatialized vibrotactile feedback systems deliver tactile information by placing multiple vibrotactile actuators on the body. As increasing numbers of actuators are required to adequately convey information in complicated applications, haptic designers find it difficult to create such systems due to limited scalability of existing toolkits. We propose VibraForge, an open-source vibrotactile toolkit that supports up to 128 vibrotactile actuators. Each actuator is encapsulated within a self-contained vibration unit and driven by its own microcontroller. By leveraging a chain-connection method, each unit receives independent vibration commands from a control unit, with fine-grained control over intensity and frequency. We also designed a GUI Editor to expedite the authoring of spatial vibrotactile patterns. Technical evaluation showed that vibration units reliably reproduced audio waveforms with low-latency and high-bandwidth data communication. Case studies of a phonemic tactile display, virtual reality fitness training, and drone teleoperation demonstrated the potential usage of VibraForge within different domains. A usability study with non-expert users highlighted the low technical barrier and customizability of the toolkit. © 2024, CC BY.

关键词： Vibrotactile aids

VibraForge: A Scalable Prototyping Toolkit For Creating Spatialized Vibrotactile Feedback Systems 25

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VibraForge: A Scalable Prototyping Toolkit For Creating Spat...

Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems

作者： Bingjian Huang Siyi Ren Yuewen Luo Qilong Cheng Hanfeng Cai Yeqi Sang Mauricio Sousa Paul H Dietz Daniel Wigdor Dynamic Graphics Project Lab University of Toronto Toronto Ontario Canada Division of Engineering Science University of Toronto Toronto Ontario Canada Mechanical Engineering University of Toronto Toronto Ontario Canada Department of Electrical and Computer Engineering University of Toronto Toronto Ontario Canada Department of Mechanical & Industrial Engineering University of Toronto Toronto Ontario Canada Reality Labs Research at Meta Toronto Ontario Canada DGP The University of Toronto Toronto Ontario Canada Department of Computer Science University of Toronto Toronto Ontario Canada

ISBN: (纸本)9798400713941

关键词： Haptics

Explainability of the Implications of Supervised and Unsupervised Face Image Quality Estimations through Activation Map Variation Analyses in Face Recognition Models

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arXiv 2021年

作者： Fu, Biying Damer, Naser Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Department of Computer Science TU Darmstadt Darmstadt Germany

It is challenging to derive explainability for unsupervised or statistical-based face image quality assessment (FIQA) methods. In this work, we propose a novel set of explainability tools to derive reasoning for different FIQA decisions and their face recognition (FR) performance implications. We avoid limiting the deployment of our tools to certain FIQA methods by basing our analyses on the behavior of FR models when processing samples with different FIQA decisions. This leads to explainability tools that can be applied for any FIQA method with any CNN-based FR solution using activation mapping to exhibit the network’s activation derived from the face embedding. To avoid the low discrimination between the general spatial activation mapping of low and high-quality images in FR models, we build our explainability tools in a higher derivative space by analyzing the variation of the FR activation maps of image sets with different quality decisions. We demonstrate our tools and analyze the findings on four FIQA methods, by presenting inter and intra-FIQA method analyses. Our proposed tools and the analyses based on them point out, among other conclusions, that high-quality images typically cause consistent low activation on the areas outside of the central face region, while low-quality images, despite general low activation, have high variations of activation in such areas. Our explainability tools also extend to analyzing single images where we show that low-quality images tend to have an FR model spatial activation that strongly differs from what is expected from a high-quality image where this difference also tends to appear more in areas outside of the central face region and does correspond to issues like extreme poses and facial occlusions. The implementation of the proposed tools is accessible here. © 2021, CC BY.

关键词： Face recognition

Mask-invariant Face Recognition through Template-level Knowledge Distillation

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arXiv 2021年

作者： Huber, Marco Boutros, Fadi Kirchbuchner, Florian Damer, Naser Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Department of Computer Science TU Darmstadt Darmstadt Germany

The emergence of the global COVID-19 pandemic poses new challenges for biometrics. Not only are contactless biometric identification options becoming more important, but face recognition has also recently been confronted with the frequent wearing of masks. These masks affect the performance of previous face recognition systems, as they hide important identity information. In this paper, we propose a mask-invariant face recognition solution (MaskInv) that utilizes template-level knowledge distillation within a training paradigm that aims at producing embeddings of masked faces that are similar to those of non-masked faces of the same identities. In addition to the distilled knowledge, the student network benefits from additional guidance by margin-based identity classification loss, ElasticFace, using masked and non-masked faces. In a step-wise ablation study on two real masked face databases and five mainstream databases with synthetic masks, we prove the rationalization of our MaskInv approach. Our proposed solution outperforms previous state-of-the-art (SOTA) academic solutions in the recent MFRC-21 challenge in both scenarios, masked vs masked and masked vs non-masked, and also outperforms the previous solution on the MFR2 dataset. Furthermore, we demonstrate that the proposed model can still perform well on unmasked faces with only a minor loss in verification performance. The code, the trained models, as well as the evaluation protocol on the synthetically masked data are publicly available: https://***/ fdbtrs/Masked-Face-Recognition-KD. Copyright © 2021, The Authors. All rights reserved.

关键词： Face recognition

CR-FIQA: Face Image Quality Assessment by Learning Sample Relative Classifiability

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arXiv 2021年

作者： Boutros, Fadi Fang, Meiling Klemt, Marcel Fu, Biying Damer, Naser Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Department of Computer Science TU Darmstadt Darmstadt Germany

Face image quality assessment (FIQA) estimates the utility of the captured image in achieving reliable and accurate recognition performance. This work proposes a novel FIQA method, CR-FIQA, that estimates the face image quality of a sample by learning to predict its relative classifiability. This classifiability is measured based on the allocation of the training sample feature representation in angular space with respect to its class center and the nearest negative class center. We experimentally illustrate the correlation between the face image quality and the sample relative classifiability. As such property is only observable for the training dataset, we propose to learn this property by probing internal network observations during the training process and utilizing it to predict the quality of unseen samples. Through extensive evaluation experiments on eight benchmarks and four face recognition models, we demonstrate the superiority of our proposed CR-FIQA over state-of-the-art (SOTA) FIQA algorithms. 1 Copyright © 2021, The Authors. All rights reserved.

关键词： Face recognition

Partial attack supervision and regional weighted inference for masked face presentation attack detection

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arXiv 2021年

作者： Fang, Meiling Boutros, Fadi Kuijper, Arjan Damer, Naser Fraunhofer Institute for Computer Graphics Research IGD Darmstadt Germany Department of Computer Science TU Darmstadt Darmstadt Germany

Wearing a mask has proven to be one of the most effective ways to prevent the transmission of SARSCoV-2 coronavirus. However, wearing a mask poses challenges for different face recognition tasks and raises concerns about the performance of masked face presentation detection (PAD). The main issues facing the mask face PAD are the wrongly classified bona fide masked faces and the wrongly classified partial attacks (covered by real masks). This work addresses these issues by proposing a method that considers partial attack labels to supervise the PAD model training, as well as regional weighted inference to further improve the PAD performance by varying the focus on different facial areas. Our proposed method is not directly linked to specific network architecture and thus can be directly incorporated into any common or custom-designed network. In our work, two neural networks (DeepPixBis [21] and MixFaceNet [4]) are selected as backbones. The experiments are demonstrated on the collaborative real mask attack (CRMA) database [17]. Our proposed method outperforms established PAD methods in the CRMA database by reducing the mentioned shortcomings when facing masked faces. Moreover, we present a detailed step-wise ablation study pointing out the individual and joint benefits of the proposed concepts on the overall PAD performance. Copyright © 2021, The Authors. All rights reserved.

关键词： Facings