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Found 13 papers, 4 papers with code
AttackNet: Enhancing Biometric Security via Tailored Convolutional Neural Network Architectures for Liveness Detection
Biometric security is the cornerstone of modern identity verification and authentication systems, where the integrity and reliability of biometric samples is of paramount importance.
Embedding Non-Distortive Cancelable Face Template Generation
Biometric authentication systems are crucial for security, but developing them involves various complexities, including privacy, security, and achieving high accuracy without directly storing pure biometric data in storage.
Cross-Database Liveness Detection: Insights from Comparative Biometric Analysis
In an era where biometric security serves as a keystone of modern identity verification systems, ensuring the authenticity of these biometric samples is paramount.
Unrecognizable Yet Identifiable: Image Distortion with Preserved Embeddings
In the realm of security applications, biometric authentication systems play a crucial role, yet one often encounters challenges concerning privacy and security while developing one.
A Federated Learning Framework for Stenosis Detection
Our results showed that the FL framework does not substantially affects clients 2 performance, which already achieved good performance with local training; for client 1, instead, FL framework increases the performance with respect to local model of +3. 76%, +17. 21% and +10. 80%, respectively, reaching P rec = 73. 56, Rec = 67. 01 and F1 = 70. 13.
A store-and-forward cloud-based telemonitoring system for automatic assessing dysarthria evolution in neurological diseases from video-recording analysis
This architecture, called facial landmark Mask RCNN, aims at locating facial landmarks as a prior for assessing the orofacial functions related to speech and examining dysarthria evolution in neurological diseases.
Trusted Data Forever: Is AI the Answer?
Archival institutions and programs worldwide work to ensure that the records of governments, organizations, communities, and individuals are preserved for future generations as cultural heritage, as sources of rights, and as vehicles for holding the past accountable and to inform the future.
A Review on Deep-Learning Algorithms for Fetal Ultrasound-Image Analysis
This paper ends with a critical summary of the current state of the art on DL algorithms for fetal US image analysis and a discussion on current challenges that have to be tackled by researchers working in the field to translate the research methodology into the actual clinical practice.
Real-Time Human Pose Estimation on a Smart Walker using Convolutional Neural Networks
We present a novel approach to patient monitoring and data-driven human-in-the-loop control in the context of smart walkers.
Comparison of different CNNs for breast tumor classification from ultrasound images
The best performance was obtained by fine tuning VGG-16, with an accuracy of 0. 919 and an AUC of 0. 934.
Preterm infants' pose estimation with spatio-temporal features
Assessment of the proposed framework is performed through a comprehensive study with sixteen depth videos acquired in the actual clinical practice from sixteen preterm infants (the babyPose dataset).
Preterm infants' limb-pose estimation from depth images using convolutional neural networks
Preterm infants' limb-pose estimation is a crucial but challenging task, which may improve patients' care and facilitate clinicians in infant's movements monitoring.
Shopper Analytics: a customer activity recognition system using a distributed RGB-D camera network
The aim of this paper is to present an integrated system consisted of a RGB-D camera and a software able to monitor shoppers in intelligent retail environments.
