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Enhancing Biometric-Capsule-based Authentication and Facial Recognition via Deep Learning
2019
Proceedings of the 24th ACM Symposium on Access Control Models and Technologies - SACMAT '19
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Moreover, we incorporate state-of-art deep learning techniques into a BioCapsule-based facial authentication system to further enhance secure recognition accuracy. ...
In recent years, developers have used the proliferation of biometric sensors in smart devices, along with recent advances in deep learning, to implement an array of biometrics-based authentication systems ...
NSF grant (NSF-CICI #1839746) and a Purdue University SoS near-the-miss grant. ...
doi:10.1145/3322431.3325417
dblp:conf/sacmat/PhillipsZ0L19
fatcat:j5m3da25fve3xpbdgo3htlb77i
CAPSULE NETWORK BASED BIOMETRIC RECOGNITION SYSTEM
2019
Journal of Artificial Intelligence and Capsule Networks
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Currently the deep learning techniques that are capable of strongly generalizing and automatically learning, with the enhanced accuracy is utilized for the biometric recognition to develop an efficient ...
The frame work put forward in the paper utilizes the capsule network with the fuzzified image enhancement for the retina based biometric recognition as it is a highly secure and reliable basis of person ...
"Enhancing Biometric-Capsule-based Authentication and Facial Recognition via Deep Learning." In Proceedings of the 24th ACM Symposium on Access Control Models and Technologies, pp. 141-146. ...
doi:10.36548/jaicn.2019.2.004
fatcat:mk2xq54g2rdeloj4a52mldfnp4
A Survey of Biometric Recognition Using Deep Learning
2020
EAI Endorsed Transactions on Energy Web
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The paper starts with biometric basics, transfer learning in deep biometrics, an overview of convolutional neural networks, and then survey work. ...
Since biometrics deals with a person's traits, it mainly involves supervised learning and may exploit deep learning effectiveness in other similar fields. ...
Phillips et al. (24) used facial recognition in the bio-capsule technique, using deep learning to enhance the existing system's security. ...
doi:10.4108/eai.27-10-2020.166775
fatcat:aihqgrk6pvbxpa54umpemr4s7a
Biometrics Recognition Using Deep Learning: A Survey
[article]
2021
arXiv
pre-print
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2020 pre-print arXiv:1912.00271v2 fatcat:rre5cqafrzfrnpxma5b3ztglcmOther Versions
Deep learning-based models have increasingly been leveraged to improve the accuracy of different biometric recognition systems in recent years. ...
Deep learning-based models have been very successful in achieving state-of-the-art results in many of the computer vision, speech recognition, and natural language processing tasks in the last few years ...
Rama Chellappa, and Dr. Nalini Ratha for reviewing this work, and providing very helpful comments and suggestions. ...
arXiv:1912.00271v3
fatcat:nobon7vrrrdnxe4pr3q2anl63y
Capsule Network-Based Deep Transfer Learning Model for Face Recognition
2022
Wireless Communications and Mobile Computing
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In this regard, this research introduces the GWOECN-FR approach, a unique grey wolf optimization with an enhanced capsule network-based deep transfer learning model for real-time face recognition. ...
The FR technology is widely applicable in a variety of fields, including security, biometrics, authentication, law enforcement, smart cards, and surveillance. ...
This study designs an effective grey wolf optimization with an enhanced capsule network-based deep transfer learning model for real-time face recognition, named the GWOECN-FR technique. ...
doi:10.1155/2022/2086613
fatcat:awyjjvphyfcmli6m4h5bi3mh6u
Design and Implementation of Deep Learning Based Contactless Authentication System Using Hand Gestures
2021
Electronics
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This work presents the design and implementation of a complete end-to-end deep learning based edge computing system that can verify a user contactlessly using 'authentication code'. ...
The proposed deep learning model is based on the bottleneck module which is inspired by the deep residual networks. ...
Below mentioned are some of the contemporary biometric authentication systems that use deep learning models, ref. [16] uses CNN for facial biometric authentication, ref. ...
doi:10.3390/electronics10020182
fatcat:ntkc5wsoajefhe34gvmzupwnye
Analysis of Convolutional Neural Network based Image Classification Techniques
2021
Journal of Innovative Image Processing
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As a result, several convolutional neural network-based classifiers are proposed to identify the fruits by visualizing via the camera for establishing a quick billing procedure in order to overcome this ...
In the supermarket industry, item identification and billing are generally done manually, which takes a lot of time and effort. ...
To improve the accuracy of automatic vegetable recognition and classification, this paper [20] presents a deep learning-based method for recognizing and classifying the vegetable images. ...
doi:10.36548/jiip.2021.2.003
fatcat:3m53eugjyrfkrf243u3vqzftay
DeepFake Detection for Human Face Images and Videos: A Survey
2022
IEEE Access
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We hope that the knowledge encompassed in this survey will accelerate the use of deep learning in face image and video DeepFake detection methods. ...
DeepFake is a generative deep learning algorithm that creates or modifies face features in a superrealistic form, in which it is difficult to distinguish between real and fake features. ...
Facial recognition [110] is essential for face image and video detection before applying a traditional or a deep fake method. ...
doi:10.1109/access.2022.3151186
fatcat:imz6hdtofrbxfcfi6kput2mffi
Generation and Detection of Media Clones
2021
IEICE transactions on information and systems
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With the spread of high-performance sensors and social network services (SNS) and the remarkable advances in machine learning technologies, fake media such as fake videos, spoofed voices, and fake reviews ...
that are generated using high-quality learning data and are very close to the real thing are causing serious social problems. ...
and paragraphs can also be automatically generated using recently developed deep-learning-based neural language models. ...
doi:10.1587/transinf.2020mui0002
fatcat:2tom7k5wrbhbbiha6g2txlgaqi
Convolutional Neural Network based on Diverse Gabor Filters for Deepfake Recognition
2022
IEEE Access
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The intuition is to use deep learning to fix the problems created by deep learning. ...
Media synthesis and manipulation has reached unprecedented levels of realism owing to the proliferation of deep learning. Deepfake has been the de-facto tool for media manipulation. ...
Finally, outputs of the three capsules are dynamically routed to the output capsules. The two output capsules, one for real images and one for fake images, indicate the authenticity of images. ...
doi:10.1109/access.2022.3152029
fatcat:75f7ldvahrgvvni7b4tp6vlnje
Deep Learning for Deepfakes Creation and Detection: A Survey
[article]
2022
arXiv
pre-print
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One of those deep learning-powered applications recently emerged is deepfake. Deepfake algorithms can create fake images and videos that humans cannot distinguish them from authentic ones. ...
Deep learning advances however have also been employed to create software that can cause threats to privacy, democracy and national security. ...
Temporal, behavioral biometric based on facial expressions and head movements are learned using ResNet-101 [118] while static facial biometric is obtained using VGG [65] . ...
arXiv:1909.11573v4
fatcat:wbxcljyajnalfednnddyyndxfe
2021 Index IEEE Signal Processing Letters Vol. 28
2021
IEEE Signal Processing Letters
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The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. ...
The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. ...
., +, LSP 2021 454-458 Biometrics (access control) A Deep Feature Fusion Network Based on Multiple Attention Mechanisms for Joint Iris-Periocular Biometric Recognition. ...
doi:10.1109/lsp.2022.3145253
fatcat:a3xqvok75vgepcckwnhh2mty74
Iris Recognition Development Techniques: A Comprehensive Review
2021
Complexity
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This article also explains the two approaches of iris recognition which are the traditional approach and the deep learning approach. ...
In addition, the researchers discuss the advantages and disadvantages of previous techniques as well as the limitations and benefits of both the traditional and deep learning approaches of iris recognition ...
[35] introduced the F-CNN and F-Capsule to increase the robustness of deep learning training as opposed to CNN and capsule. e suggested F-CNN and F-Capsule contribute to the training process of the ...
doi:10.1155/2021/6641247
fatcat:xil2fsokf5eetc2cx4br7bcquy
Learning Neural Textual Representations for Citation Recommendation
2021
2020 25th International Conference on Pattern Recognition (ICPR)
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Applications
DAY 1 -Jan 12, 2021
Banerjee, Sudipta; Ross, Arun
1640
One-Shot Representational Learning for Joint Biometric and Device
Authentication
DAY 1 -Jan 12, 2021
Vahdani, Elahe; Jing ...
Daniel; Lam, Kin-
Man
1231
Deep Multi-Task Learning for Facial Expression Recognition and
Synthesis Based on Selective Feature Sharing
DAY 3 -Jan 14, 2021
Kondo, Kazuaki; Nakamura, Taichi;
Nakamura ...
doi:10.1109/icpr48806.2021.9412725
fatcat:3vge2tpd2zf7jcv5btcixnaikm
A New Deep Learning-Based Methodology for Video Deepfake Detection Using XGBoost
2021
Sensors
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Due to their devastating impacts on the world, distinguishing between real and deepfake videos has become a fundamental issue. ...
Currently, face-swapping deepfake techniques are widely spread, generating a significant number of highly realistic fake videos that threaten the privacy of people and countries. ...
Faces play an important role in humans interactions and biometrics-based human authentication and identification services. ...
doi:10.3390/s21165413
pmid:34450855
pmcid:PMC8398984
fatcat:pnifjwgcu5ehjfjemcj4isqtla
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