AIMC Topic: Biometry

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Accuracy of Artificial Intelligence Formulas and Axial Length Adjustments for Highly Myopic Eyes.

American journal of ophthalmology
PURPOSE: To compare the accuracy of artificial intelligence formulas (Kane formula and Radial Basis Function [RBF] 2.0) and other formulas, including the original and modified Wang-Koch (MWK) adjustment formulas for Holladay 1 (H1-MWK) and SRK/T (SRK...

ECG Biometrics Using Deep Learning and Relative Score Threshold Classification.

Sensors (Basel, Switzerland)
The field of biometrics is a pattern recognition problem, where the individual traits are coded, registered, and compared with other database records. Due to the difficulties in reproducing Electrocardiograms (ECG), their usage has been emerging in t...

Can Ensemble Deep Learning Identify People by Their Gait Using Data Collected from Multi-Modal Sensors in Their Insole?

Sensors (Basel, Switzerland)
Gait is a characteristic that has been utilized for identifying individuals. As human gait information is now able to be captured by several types of devices, many studies have proposed biometric identification methods using gait information. As rese...

Using a Rotating 3D LiDAR on a Mobile Robot for Estimation of Person's Body Angle and Gender.

Sensors (Basel, Switzerland)
We studied the use of a rotating multi-layer 3D Light Detection And Ranging (LiDAR) sensor (specifically the Velodyne HDL-32E) mounted on a social robot for the estimation of features of people around the robot. While LiDARs are often used for robot ...

Deep user identification model with multiple biometric data.

BMC bioinformatics
BACKGROUND: Recognition is an essential function of human beings. Humans easily recognize a person using various inputs such as voice, face, or gesture. In this study, we mainly focus on DL model with multi-modality which has many benefits including ...

Emphysema quantification using low-dose computed tomography with deep learning-based kernel conversion comparison.

European radiology
OBJECTIVE: This study determined the effect of dose reduction and kernel selection on quantifying emphysema using low-dose computed tomography (LDCT) and evaluated the efficiency of a deep learning-based kernel conversion technique in normalizing ker...

Uniformity Attentive Learning-Based Siamese Network for Person Re-Identification.

Sensors (Basel, Switzerland)
Person re-identification (Re-ID) has a problem that makes learning difficult such as misalignment and occlusion. To solve these problems, it is important to focus on robust features in intra-class variation. Existing attention-based Re-ID methods foc...

Achieving accurate estimates of fetal gestational age and personalised predictions of fetal growth based on data from an international prospective cohort study: a population-based machine learning study.

The Lancet. Digital health
BACKGROUND: Preterm birth is a major global health challenge, the leading cause of death in children under 5 years of age, and a key measure of a population's general health and nutritional status. Current clinical methods of estimating fetal gestati...

Spatio-temporal visual attention modelling of standard biometry plane-finding navigation.

Medical image analysis
We present a novel multi-task neural network called Temporal SonoEyeNet (TSEN) with a primary task to describe the visual navigation process of sonographers by learning to generate visual attention maps of ultrasound images around standard biometry p...

ECG Authentication Hardware Design With Low-Power Signal Processing and Neural Network Optimization With Low Precision and Structured Compression.

IEEE transactions on biomedical circuits and systems
Biometrics such as facial features, fingerprint, and iris are being used increasingly in modern authentication systems. These methods are now popular and have found their way into many portable electronics such as smartphones, tablets, and laptops. F...