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Biometry

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ECG-based Biometric Recognition without QRS Segmentation: A Deep Learning-Based Approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Electrocardiogram (ECG)-based identification systems have been widely studied in the literature. Usually, an ECG trace needs to be segmented according to the detected R peaks to enable feature extraction from the ECGs of duration equal to nearly one ...

Random vector functional link with ε-insensitive Huber loss function for biomedical data classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Biomedical data classification has been a trending topic among researchers during the last decade. Biomedical datasets may contain several features noises. Hence, the conventional machine learning model cannot efficiently ha...

System on Chip (SoC) for Invisible Electrocardiography (ECG) Biometrics.

Sensors (Basel, Switzerland)
Biometric identification systems are a fundamental building block of modern security. However, conventional biometric methods cannot easily cope with their intrinsic security liabilities, as they can be affected by environmental factors, can be easil...

Prediction of the axial lens position after cataract surgery using deep learning algorithms and multilinear regression.

Acta ophthalmologica
BACKGROUND: The prediction of anatomical axial intraocular lens position (ALP) is one of the major challenges in cataract surgery. The purpose of this study was to develop and test prediction algorithms for ALP based on deep learning strategies.

Deep learning fetal ultrasound video model match human observers in biometric measurements.

Physics in medicine and biology
This work investigates the use of deep convolutional neural networks (CNN) to automatically perform measurements of fetal body parts, including head circumference, biparietal diameter, abdominal circumference and femur length, and to estimate gestati...

Template-Driven Knowledge Distillation for Compact and Accurate Periocular Biometrics Deep-Learning Models.

Sensors (Basel, Switzerland)
This work addresses the challenge of building an accurate and generalizable periocular recognition model with a small number of learnable parameters. Deeper (larger) models are typically more capable of learning complex information. For this reason, ...

Electrocardiogram Biometrics Using Transformer's Self-Attention Mechanism for Sequence Pair Feature Extractor and Flexible Enrollment Scope Identification.

Sensors (Basel, Switzerland)
The existing electrocardiogram (ECG) biometrics do not perform well when ECG changes after the enrollment phase because the feature extraction is not able to relate ECG collected during enrollment and ECG collected during classification. In this rese...

Advances in Vision-Based Gait Recognition: From Handcrafted to Deep Learning.

Sensors (Basel, Switzerland)
Identifying people's identity by using behavioral biometrics has attracted many researchers' attention in the biometrics industry. Gait is a behavioral trait, whereby an individual is identified based on their walking style. Over the years, gait reco...

An affordable and easy-to-use tool for automatic fish length and weight estimation in mariculture.

Scientific reports
Common aquaculture practices involve measuring fish biometrics at different growth stages, which is crucial for feeding regime management and for improving farmed fish welfare. Fish measurements are usually carried out manually on individual fish. Ho...

Deep learning-based patient re-identification is able to exploit the biometric nature of medical chest X-ray data.

Scientific reports
With the rise and ever-increasing potential of deep learning techniques in recent years, publicly available medical datasets became a key factor to enable reproducible development of diagnostic algorithms in the medical domain. Medical data contains ...