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Artículos de revistas sobre el tema "Soft Biometry"

Autor: Grafiati
Publicado: 11 de marzo de 2023
Última modificación: 31 de julio de 2025

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1

Ahmed, Aseef, Sinan Akosman, Sasha Narain, and Keith J. Wroblewski. "Presence of a soft contact lens during biometry." Global Journal of Cataract Surgery and Research in Ophthalmology 2 (September 13, 2023): 48–49. http://dx.doi.org/10.25259/gjcsro_10_2023.

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A case of an intraocular lens (IOL) power calculation error due to the presence of a soft contact lens (CL) is described. During preparation of a routine cataract surgery for a patient in the operating room, a soft CL was discovered on the patient’s surgical eye by the scrub nurse. Further, questioning revealed that the patient was a regular CL wearer and had possibly worn them during pre-operative biometric measurement, suggesting a potential error in his IOL calculation. Surgery was not performed, and the patient was given a CL holiday. Examination of the pre-operative B-scan ultrasound by t
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2

Różyło-Kalinowska, Ingrid, Jakub Kuryło, Stanisław Nowak, Magdalena Piskórz, Katarzyna Portka, and Magdalena Kozek. "Ultrasonographic biometry of soft tissues in patients with gingival recessions. Preliminary report." Journal of Stomatology 72, no. 3 (2019): 106–11. http://dx.doi.org/10.5114/jos.2019.87523.

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3

Madadi, Meysam, Sergio Escalera, Jordi Gonzàlez, F. Xavier Roca, and Felipe Lumbreras. "Multi-part body segmentation based on depth maps for soft biometry analysis." Pattern Recognition Letters 56 (April 2015): 14–21. http://dx.doi.org/10.1016/j.patrec.2015.01.012.

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4

Hebbar, Shripad, Sukriti Malaviya, and Sunanda Bharatnur. "INTEGRATION OF FETAL MID THIGH SOFT TISSUE THICKNESS IN ULTRASOUND BIRTH WEIGHT ESTIMATION FORMULA INCREASES THE ACCURACY OF FETAL WEIGHT ESTIMATION NEAR TERM." Asian Journal of Pharmaceutical and Clinical Research 11, no. 4 (2018): 446. http://dx.doi.org/10.22159/ajpcr.2018.v11i4.23776.

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Objective: The objective of the study was to find whether incorporation of MTSTT in fetal weight estimation formulae which are traditionally based on biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), and femur length (FL) improves birth weight (BW) estimation. Methods: In a prospective observational study, MTSTT was measured within 1 week of delivery in 100 women with term singleton pregnancy along with other standard biometric parameters, i.e. BPD, HC, AC and FL, and MTSTT. Multiple regression analysis was carried out using PHOEBE regression software using diff
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5

Belov, D. F., V. P. Nikolaenko, and V. V. Kovaleva. "Evaluation and Refractive Results Comparison of MIOL-­SOFT-­2­-13 IOL Implantation with Foreign Models." Ophthalmology in Russia 21, no. 2 (2024): 289–95. http://dx.doi.org/10.18008/1816-5095-2024-2-289-295.

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Purpose. Evaluation and refractive results comparison of MIOL-­SOFT-­2­-13 (Reper­NN, Russia) IOL implantation with foreign models. Material and methods. The study included 816 patients (816 eyes) who underwent phacoemulsification (PE) with IOL implantation, divided into four groups depending on IOL model: MIOL­-SOFT-2-­13 (Reper­-NN, Russia) (n = 199); SA60AT (Alcon, USA) (n = 237); Adapt AO (Bausch&Lomb, USA) (n = 179); Acryfold 601 (Appasamy Associates, India) (n = 201). All patients underwent optical biometry using IOL­-Master 500 (Carl Zeiss, Germany). A month after PE spherical equiv
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6

Cinar, Hatice Burcu, and Mekin Sezik. "Correlation of Fractional Limb Volume Measurements with Neonatal Morphometric Indices." Gynecologic and Obstetric Investigation 86, no. 1-2 (2021): 94–99. http://dx.doi.org/10.1159/000512749.

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<b><i>Objectives:</i></b> Fractional thigh volume (TVol) and fractional arm volume (AVol) measurements by three-dimensional (3D) ultrasound can reveal valuable information on fetal soft tissue development. However, it is not clear whether TVol or AVol provides better estimates of fetal body proportion and adiposity, independent of routine two-dimensional (2D) ultrasound biometry. The primary objective of the current study was to determine the correlations between fractional limb volumes (FLVs) and neonatal anthropometric parameters. <b><i>Design:</i>&l
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7

Lewis, Jennifer R., Andrea E. Knellinger, Ashraf M. Mahmoud, and Thomas F. Mauger. "Effect of Soft Contact Lenses on Optical Measurements of Axial Length and Keratometry for Biometry in Eyes with Corneal Irregularities." Investigative Opthalmology & Visual Science 49, no. 8 (2008): 3371. http://dx.doi.org/10.1167/iovs.07-1247.

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8

Garcia Flores, Jose, Ritu Mogra, Monica Sadowski, and Jon Hyett. "Prediction of Birth Weight and Neonatal Adiposity Using Ultrasound Assessment of Soft Tissue Parameters in Addition to Two-Dimensional Conventional Biometry." Fetal Diagnosis and Therapy 48, no. 3 (2021): 201–8. http://dx.doi.org/10.1159/000510637.

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<b><i>Introduction:</i></b> We aim to evaluate the supplementary predictive value of soft tissue markers, including fetal limb volumes, for fetal birth weight and fat tissue weight. <b><i>Methods:</i></b> This is a prospective study of 60 patients undergoing term induction of labor. Ultrasound was performed 48 h before birth, and 2D sonographic measurements, subcutaneous tissue thickness, and 3D fetal limb volumes were taken. Birth weight and neonatal fat weight were assessed by plethysmography. Clinical data were collected. The relation between
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9

Tarutta, E. P., S. V. Milash, and M. V. Epishina. "Accommodation Dynamics in Children Wearing Bifocal Soft Contact Lenses with High Addition Power." EYE GLAZ 23, no. 1 (2021): 7–14. http://dx.doi.org/10.33791/2222-4408-2021-1-7-14.

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Purpose: to evaluate dynamics of subjective and objective accommodation in children wearing bifocal soft contact lenses (BSCLs) for myopia control with +4.00 D addition power. M e t h o d s: the study involved 22 patients (44 eyes).Mean age amounted to 10.1 ± 1.46 years and mean myopic refraction amounted to –3.21 ± 1.23 D. Patients were fitted Prima BIO Bi-focal BSCLs (OKVision Retail, Russia). All patients underwent cycloplegic refraction assessed with Auto Ref/Keratometer ARK 530A (Nidek, Japan), had axial length measured with IOL Master 500 optical biometry device (Carl Zeiss, Germany), ha
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10

Tamano, Luana Tieko Omena, Beethoven Brandão Correia de Lima, Joseane Da Silva, and Daniel de Magalhães Araujo. "FISHING, PROCESSING, COMMERCIALIZATION AND A PROPOSE TO FISHERY WASTE REUSE OF SURURU Mytella falcata IN THE MUNDAÚ LAGOON, MACEIÓ – AL, BRAZIL." Caminhos de Geografia 21, no. 76 (2020): 306–20. http://dx.doi.org/10.14393/rcg217652255.

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A diagnosis was made on the fishing, processing, commercialization and generation of residues of the sururu fishery in Mundaú lagoon, Maceió-AL. Thirty nine fishermen were interviewed and also incursions were made for observations. Furthermore, sururus were collected to perform biometry. Residue of the sururu processing was collected to the fabrication of sururu waste meal (SWM), posteriorilly its bromatological composition was analysed. Fishermens of sururus fish 4.56 times week-1 and each fishing excursion lasts 5h26min, yielding 18.61 cans (18.61 to 37.22 kg soft tissue). Besides the sururu
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11

Kharel, Milan, and Damodar Thapa Chhetry. "Description on some rescued turtles and their translocation at Turtle Rescue and Conservation Centre (TRCC), Sanischare, Jhapa." BIBECHANA 11 (May 10, 2014): 141–48. http://dx.doi.org/10.3126/bibechana.v11i0.10394.

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The present paper deals with the brief introduction of Turtle Rescue and Conservation Centre (TRCC) and description of some rescued turtles. Nine specimens of turtles belonging to five genera were rescued and translocated to the centre till date including 9.3 kg male Indian Peacock soft-shelled turtle (Nilssonia hurum) for the first time from Jhapa district. The rescue operations were conducted for the translocation of turtles confiscated from the local market, censorial collectors, fisherman and public residence. The high resolution photographs of captured specimens, their necessary biometry
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12

Chuprov, A. D., V. L. Kim, and A. E. Voronina. "Evaluation of the efficiency of refractive error correction using phakic intraocular lens implantation." Acta Biomedica Scientifica 7, no. 2 (2022): 167–73. http://dx.doi.org/10.29413/abs.2022-7.2.17.

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Background. Myopia is the most common clinical refractive error of the eye. Only in Russia, there are about 15 million myopic people. Currently, in addition to traditional correction (glasses, soft contact lenses), keratorefractive surgery actively develops; however, due to the initial parameters of the cornea or the magnitude of the refractive error, it may be contraindicated to the patient. Nowadays an alternative to these correction methods for young patients with refractive errors of high and ultra-high degrees is the implantation of a phakic intraocular lens.The aim. To evaluate the effic
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13

Sobabe, Abdou-Aziz, Tahirou Djara, Blaise Blochaou, and Antoine Vianou. "Soft Biometrics Authentication." Journal of Information Technology Research 15, no. 1 (2022): 1–17. http://dx.doi.org/10.4018/jitr.298620.

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This manuscript presents the design of a new approach of human skin color authentication. Skin color is one of the most popular soft biometric modalities. Since a soft biometric modality alone cannot reliably authenticate an individual, this new system is designed to combine skin color results with other pure biometric modalities to increase recognition performance. In the classification process, we first perform facial skin detection by segmentation using the thresholding method in the HSV color space. Then, the K-means algorithm of the clustering method is used to determine the dominant colo
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14

Yaacob, Mohd Noorulfakhri, Syed Zulkarnain Syed Idrus, Wan Azani Wan Mustafa, Mohd Aminudin Jamlos, and Mohd Helmy Abd Wahab. "Identification of the Exclusivity of Individual’s Typing Style Using Soft Biometric Elements." Annals of Emerging Technologies in Computing 5, no. 5 (2021): 10–26. http://dx.doi.org/10.33166/aetic.2021.05.002.

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Biometric is used as a main security fence in a computer system. The unique characteristics of a person can be distinguished from each other. Human’s biometrics can be categorized into three types: morphological, biological and behavioural. Morphological biometrics uses physical features for recognition. Biological biometrics used to identify user based on biological features. Behavioural biometrics such as gender, culture, height and weight can be used as an additional security measure within a system. These biometric behavioural features are also known as soft biometric. This study uses soft
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15

Malcangi, Mario. "Soft-computing methods for robust authentication using soft-biometric data." Neural Computing and Applications 20, no. 6 (2011): 865–77. http://dx.doi.org/10.1007/s00521-010-0514-1.

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16

Niinuma, Koichiro, Unsang Park, and Anil K. Jain. "Soft Biometric Traits for Continuous User Authentication." IEEE Transactions on Information Forensics and Security 5, no. 4 (2010): 771–80. http://dx.doi.org/10.1109/tifs.2010.2075927.

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17

Rai, Ankush, and Jagadeesh Kannan R. "SURVEY OF SOFT BIOMETRIC TECHNIQUES FOR GENDER IDENTIFICATION." Asian Journal of Pharmaceutical and Clinical Research 10, no. 13 (2017): 296. http://dx.doi.org/10.22159/ajpcr.2017.v10s1.19741.

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Biometrics checks can be productively utilized for localization of intrusion in access control systems by utilizing soft computing frameworks.Biometrics procedures can be to a great extent separated into conventional and soft biometrics. The study presents a survey of the available softtechniques and comparison for gender identification from biometric techniques.
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18

Venkata Ramudu, Dr Balasani, Mr Chiranjeevi Kondabathini, and Mr Udaya Kiran Mandhugula. "Enhancing Handwritten Signature Identification and Palm Biometric Objectives." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 12 (2023): 1–13. http://dx.doi.org/10.55041/ijsrem27802.

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Soft biometrics are already widely used as a support tool for user identification. However, it is not the only use for biometric information that is conceivable because such information can be sufficient to obtain minimal details from the user that are unrelated to his identity. Examples of what might be referred to as soft biometrics include gender, hand orientation, and emotional state. Utilizing physiologic modalities for soft-biometric work is extremely prevalent, prediction, but behavioral data is frequently disregarded. Keystroke dynamics and handwriting signature are two potential behav
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19

Kumar, Sandeep, Shilpa Rani, Arpit Jain, et al. "Face Spoofing, Age, Gender and Facial Expression Recognition Using Advance Neural Network Architecture-Based Biometric System." Sensors 22, no. 14 (2022): 5160. http://dx.doi.org/10.3390/s22145160.

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Nowadays, the demand for soft-biometric-based devices is increasing rapidly because of the huge use of electronics items such as mobiles, laptops and electronic gadgets in daily life. Recently, the healthcare department also emerged with soft-biometric technology, i.e., face biometrics, because the entire data, i.e., (gender, age, face expression and spoofing) of patients, doctors and other staff in hospitals is managed and forwarded through digital systems to reduce paperwork. This concept makes the relation friendlier between the patient and doctors and makes access to medical reports and tr
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20

Kuznetsov, A. R., A. A. Dzilihov, D. V. Tulin, and N. V. Nevin. "Eye biometry shift after scleral buckling procedure." Modern technologies in ophtalmology, no. 3 (May 14, 2024): 72–77. http://dx.doi.org/10.25276/2312-4911-2024-3-72-77.

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Background. There are a great number publications present results of various types of optical and ultrasound biometry before and after scleral buckling procedure. Purpose. To evaluate ocular biometrics using different methods before and after scleral buckling procedure. Material and methods. Biometry was performed for 37 eyes of 37 patients before and after surgical treatment of rhegmatogenous retinal detachment. We used 4 types of optical (IOLMaster 500, IOLMaster 700, Lenstar LS 900 and REVO SOCT Copernicus) and 2 types of ultrasound biometry (A- and B-scan). Results.According to the all bio
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21

Dee, Timothy, Ian Richardson, and Akhilesh Tyagi. "Continuous Nonintrusive Mobile Device Soft Keyboard Biometric Authentication." Cryptography 6, no. 2 (2022): 14. http://dx.doi.org/10.3390/cryptography6020014.

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Mobile banking, shopping, and in-app purchases utilize persistent authentication states for access to sensitive data. One-shot authentication permits access for a fixed time period. For instance, a username/password-based authentication allows a user access to all the shopping and payments data in the Amazon shopping app. Traditional user passwords and lock screens are easily compromised. Snooping attacks—observing an unsuspecting user entering passwords—and smudge attacks—examining touchscreen finger oil residue—enable compromised user authentication. Mobile device interactions provide robust
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22

Denman, Simon, Michael Halstead, Clinton Fookes, and Sridha Sridharan. "Searching for people using semantic soft biometric descriptions." Pattern Recognition Letters 68 (December 2015): 306–15. http://dx.doi.org/10.1016/j.patrec.2015.06.015.

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23

Yang, Lu, Gongping Yang, Yilong Yin, and Xiaoming Xi. "Exploring soft biometric trait with finger vein recognition." Neurocomputing 135 (July 2014): 218–28. http://dx.doi.org/10.1016/j.neucom.2013.12.029.

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24

Tome, Pedro, Ruben Vera-Rodriguez, Julian Fierrez, and Javier Ortega-Garcia. "Facial soft biometric features for forensic face recognition." Forensic Science International 257 (December 2015): 271–84. http://dx.doi.org/10.1016/j.forsciint.2015.09.002.

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25

Wahab, A., G. S. Ng, and A. Jonatan. "Integrated Biometric Verification System Using Soft Computing Approach." Neural Processing Letters 25, no. 2 (2007): 111–26. http://dx.doi.org/10.1007/s11063-006-9024-7.

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26

Danelakis, Antonios, and Theoharis Theoharis. "Image-Based Somatotype as a Biometric Trait for Non-Collaborative Person Recognition at a Distance and On-The-Move." Sensors 20, no. 12 (2020): 3419. http://dx.doi.org/10.3390/s20123419.

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It has recently been shown in Re-Identification (Re-ID) work that full-body images of people reveal their somatotype, even after change in apparel. A significant advantage of this biometric trait is that it can easily be captured, even at a distance, as a full-body image of a person, taken by a standard 2D camera. In this work, full-body image-based somatotype is investigated as a novel soft biometric feature for person recognition at a distance and on-the-move. The two common scenarios of (i) identification and (ii) verification are both studied and evaluated. To this end, two different deep
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27

Halleluyah Oluwatobi, Aworinde, and Onifade O.F.W. "A Soft Computing Model of Soft Biometric Traits for Gender and Ethnicity Classification." International Journal of Engineering and Manufacturing 9, no. 2 (2019): 54–63. http://dx.doi.org/10.5815/ijem.2019.02.05.

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28

Kulikov, A. N., E. V. Danilenko, and A. R. Kuznetsov. "Eye Biometry Shift after Scleral Buckling Procedure." Ophthalmology in Russia 19, no. 3 (2022): 493–99. http://dx.doi.org/10.18008/1816-5095-2022-3-493-499.

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Background. There are a great number publications presenting results of various types of optical and ultrasound biometry before and after scleral buckling (SB).Patients and methods. Biometry was performed for 22 eyes of 22 patients before and after surgical treatment of rhegmatogenous retinal detachment. We used 4 types of optical (IOLMaster 500, IOLMaster 700, Lenstar LS 900 and REVO SOCT Copernicus) and 2 types of ultrasound biometry (A- and B-scan).Results. According to the all biometry data, there was an increase in the axial lens (AL) (the maximum value of eye elongation according to IOLM
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29

Bisogni, Carmen, Lucia Cascone, and Fabio Narducci. "Periocular Data Fusion for Age and Gender Classification." Journal of Imaging 8, no. 11 (2022): 307. http://dx.doi.org/10.3390/jimaging8110307.

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In recent years, the study of soft biometrics has gained increasing interest in the security and business sectors. These characteristics provide limited biometric information about the individual; hence, it is possible to increase performance by combining numerous data sources to overcome the accuracy limitations of a single trait. In this research, we provide a study on the fusion of periocular features taken from pupils, fixations, and blinks to achieve a demographic classification, i.e., by age and gender. A data fusion approach is implemented for this purpose. To build a trust evaluation o
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Arigbabu, Olasimbo Ayodeji, Sharifah Mumtazah Syed Ahmad, Wan Azizun Wan Adnan, Salman Yussof, Vahab Iranmanesh, and Fahad Layth Malallah. "Estimating Body Related Soft Biometric Traits in Video Frames." Scientific World Journal 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/460973.

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Soft biometrics can be used as a prescreening filter, either by using single trait or by combining several traits to aid the performance of recognition systems in an unobtrusive way. In many practical visual surveillance scenarios, facial information becomes difficult to be effectively constructed due to several varying challenges. However, from distance the visual appearance of an object can be efficiently inferred, thereby providing the possibility of estimating body related information. This paper presents an approach for estimating body related soft biometrics; specifically we propose a ne
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31

Guo, Bingchen H., Mark S. Nixon, and John N. Carter. "Soft Biometric Fusion for Subject Recognition at a Distance." IEEE Transactions on Biometrics, Behavior, and Identity Science 1, no. 4 (2019): 292–301. http://dx.doi.org/10.1109/tbiom.2019.2943934.

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32

Lyle, Jamie R., Philip E. Miller, Shrinivas J. Pundlik, and Damon L. Woodard. "Soft biometric classification using local appearance periocular region features." Pattern Recognition 45, no. 11 (2012): 3877–85. http://dx.doi.org/10.1016/j.patcog.2012.04.027.

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33

Shende, Priti, Sagar Shinde, Lalitkumar Wadhwa, et al. "Soft computing approach for feature extraction of palm biometric." Multidisciplinary Science Journal 6, no. 4 (2023): 2024049. http://dx.doi.org/10.31893/multiscience.2024049.

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The method for developing a secure and reliable identification system relies on the use of biometrics. In this case, the palm vein is used as a security measure. The proposed system is powered by a convolutional neural network, which is a type of neural network that is commonly utilized for image recognition. The palm vein's visual features are extracted using a convolutional neural network. This method can improve the recognition rate and its performance parameters. The results of an experiment conducted with this method were better than those obtained with conventional techniques.
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Alotoum, Y. M. A. A., and A. V. Krasov. "Soft Biometrics for Authentication and Identification Hand Based on the Use of the Keyboard." Proceedings of Telecommunication Universities 10, no. 6 (2024): 55–67. https://doi.org/10.31854/1813-324x-2024-10-6-55-67.

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Relevance. Nowadays, technological systems, artificial intelligence, the general availability of the Internet and penetration into the systems of banks, institutions and social networks have become a studied science and are accessible to all groups and ages. One of the main tasks was to provide a system for protecting confidential information from hackers, as well as easy access to authentication and identification of users. Biometric systems came to the fore, including mouse movement dynamics and keystroke dynamics, which reveal the typing style and mouse movement of each person. Soft biometr
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Sadeq, Fatima Esmail, and Ziyad Tariq Mustafa Al-Ta'i. "Comparison Between Face and Gait Human Recognition Using Enhanced Convolutional Neural Network." Journal of Applied Engineering and Technological Science (JAETS) 5, no. 1 (2023): 18–30. http://dx.doi.org/10.37385/jaets.v5i1.2806.

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Identifying people at distance is an important task in daily life Because of the increase in terrorism. Biometrics is a better solution to overcome personal identity problems, and this applies to soft biometrics also. Soft biometric are features that can be extracted remotely and do not require cooperation with people. This paper introduces a comparison between human face recognition and human gait recognition using soft biometric features. Nine face attributes and nine gait attributes are taken from a dataset built by researchers. The constructed dataset is composed from (66) videos for (33)
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Alsubhi, Ahuod Hameed, and Emad Sami Jaha. "Front-to-Side Hard and Soft Biometrics for Augmented Zero-Shot Side Face Recognition." Sensors 25, no. 6 (2025): 1638. https://doi.org/10.3390/s25061638.

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Face recognition is a fundamental and versatile technology widely used to identify individuals. The human face is a significant nonintrusive biometric modality, attracting numerous research studies. Still, much less focus has been on side-face views, with the majority merely or mainly concentrating on the frontal face. Despite offering fewer traits than the front viewpoint, the side viewpoint of the face is a crucial aspect of an individual’s identity and, in numerous cases, can be the only available information. Our research proposes new soft biometric traits based on the face anthropometric
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37

P., Gopinath. "Raspberry PI-Based Finger Vein Recognition System Using PCA NET." International Research Journal of Computer Science 10, no. 06 (2023): 414–18. http://dx.doi.org/10.26562/irjcs.2023.v1006.24.

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Despite simultaneously ignoring the intensity distribution that is formed by the finger tissue and, in some instances, processing it as background noise, the majority of finger vein feature extraction algorithms achieve satisfactory performance due to their ability to represent texture. This project makes use of two- directional two-dimensional Fisher Principal Component Analysis, also known as (2D) 2 FPCA, for feature extraction. This type of "noise" is presented as a novel soft biometric trait for improving finger vein recognition performance. In order to demonstrate that the intensity distr
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38

Saeed, Usman. "Facial micro-expressions as a soft biometric for person recognition." Pattern Recognition Letters 143 (March 2021): 95–103. http://dx.doi.org/10.1016/j.patrec.2020.12.021.

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39

Villalobos, Esteban, Domingo Mery, and Kevin Bowyer. "Fair Face Verification by Using Non-Sensitive Soft-Biometric Attributes." IEEE Access 10 (2022): 30168–79. http://dx.doi.org/10.1109/access.2022.3158967.

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40

Kim, Min-Gu, Hae-Min Moon, Yongwha Chung, and Sung Bum Pan. "A Survey and Proposed Framework on the Soft Biometrics Technique for Human Identification in Intelligent Video Surveillance System." Journal of Biomedicine and Biotechnology 2012 (2012): 1–7. http://dx.doi.org/10.1155/2012/614146.

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Biometrics verification can be efficiently used for intrusion detection and intruder identification in video surveillance systems. Biometrics techniques can be largely divided into traditional and the so-called soft biometrics. Whereas traditional biometrics deals with physical characteristics such as face features, eye iris, and fingerprints, soft biometrics is concerned with such information as gender, national origin, and height. Traditional biometrics is versatile and highly accurate. But it is very difficult to get traditional biometric data from a distance and without personal cooperatio
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Regina, Lionnie, Agustina Ellisa, Sediono Wahju, and Alaydrus Mudrik. "Biometric identification using augmented database." TELKOMNIKA Telecommunication, Computing, Electronics and Control 17, no. 1 (2019): 103–9. https://doi.org/10.12928/TELKOMNIKA.v17i1.11713.

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Androgenic hair pattern is one of the newest soft biometric trait that can be used to identify criminals when their faces are covered in the evidences of criminal investigation. In real-life situation, sometimes the available evidence is limited thus creating problems for authorities to identify criminal based on the limited data. This research developed the recognition system to identify individuals based on their androgenic hair pattern in a limited data situation in such a way that the limited images were expanded by the augmentation process. There were 50 images studied and expanded into 2
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42

Singh, Mahesh K., Sanjeev Kumar, and Durgesh Nandan. "Biometric Face Identification: Utilizing Soft Computing Methods for Feature-Based Recognition." Traitement du Signal 41, no. 5 (2024): 2721–28. http://dx.doi.org/10.18280/ts.410545.

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43

Kang, Jian, Brian J. Reich, and Ana-Maria Staicu. "Scalar-on-image regression via the soft-thresholded Gaussian process." Biometrika 105, no. 1 (2018): 165–84. http://dx.doi.org/10.1093/biomet/asx075.

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44

Assouma, Abdoul Kamal, Tahirou Djara, and Abdou-Aziz Sobabe. "Multi-Biometrics: Survey and Projection of a New Biometric System." International Journal of Engineering and Advanced Technology 12, no. 3 (2023): 80–87. http://dx.doi.org/10.35940/ijeat.c4008.0212323.

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Multi-biometric systems using feature-level fusion allow more accuracy and reliability in recognition performance than uni-biometric systems. But in practice, this type of fusion is difficult to implement especially when we are facing heterogeneous biometric modalities or incompatible features. The major challenge of feature fusion is to produce a representation of each modality with an excellent level of discrimination. Beyond pure biometric modalities, the use of metadata has proven to improve the performance of biometric systems. In view of these findings, our work focuses on multi-origin b
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45

Abdoul, Kamal Assouma, Djara Tahirou, and Sobabe Abdou-Aziz. "Multi-Biometrics: Survey and Projection of a New Biometric System." International Journal of Engineering and Advanced Technology (IJEAT) 12, no. 3 (2023): 80–87. https://doi.org/10.35940/ijeat.C4008.0212323.

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<strong>Abstract: </strong>Multi-biometric systems using feature-level fusion allow more accuracy and reliability in recognition performance than uni-biometric systems. But in practice, this type of fusion is difficult to implement especially when we are facing heterogeneous biometric modalities or incompatible features. The major challenge of feature fusion is to produce a representation of each modality with an excellent level of discrimination. Beyond pure biometric modalities, the use of metadata has proven to improve the performance of biometric systems. In view of these findings, our wor
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46

Khudaykulov, Jonibek Bozarovich, and Mukhriddin Rakhmon Ugli Zukhriddinov. "Effect of mineral fertilizer rate on biometric indicators of soft wheat varieties." ACADEMICIA: An International Multidisciplinary Research Journal 10, no. 11 (2020): 981–88. http://dx.doi.org/10.5958/2249-7137.2020.01450.0.

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47

Dantcheva, Antitza, Petros Elia, and Arun Ross. "What Else Does Your Biometric Data Reveal? A Survey on Soft Biometrics." IEEE Transactions on Information Forensics and Security 11, no. 3 (2016): 441–67. http://dx.doi.org/10.1109/tifs.2015.2480381.

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48

Drosou, Anastasios, D. Tzovaras, K. Moustakas, and M. Petrou. "Systematic Error Analysis for the Enhancement of Biometric Systems Using Soft Biometrics." IEEE Signal Processing Letters 19, no. 12 (2012): 833–36. http://dx.doi.org/10.1109/lsp.2012.2221701.

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49

Giot, Romain, and Christophe Rosenberger. "A new soft biometric approach for keystroke dynamics based on gender recognition." International Journal of Information Technology and Management 11, no. 1/2 (2012): 35. http://dx.doi.org/10.1504/ijitm.2012.044062.

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50

Clemons, William, and Jeremy Straub. "Human Male Body Images from Multiple Perspectives with Multiple Lighting Settings." Data 4, no. 1 (2018): 3. http://dx.doi.org/10.3390/data4010003.

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There are multiple technological ways to identify humans and verify claimed identities. The dataset presented herein facilitates work on hard and soft biometric human identification and identity verification. It is comprised of full-body images of multiple fully clothed males from a constrained age range. The images have been taken from multiple perspectives with varied lighting brightness and temperature.
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