There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

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Modern Applied Statistics With S

2 1 The innovative transport systems and the CityMobil project 10 1.1 The research questions 10 2 The state of art in the field of automatic transport systems 12 2.1 Case studies and demand studies for innovative transport systems 12 3 The design and implementation of surveys 14 3.1 Definition of experimental design 14 3.2 Questionnaire design and delivery 16 3.3 First analyses on the collected sample 18 4 Calibration of Logit Multionomial demand models 21 4.1 Methodology 21 4.2 Calibration of the “full” model. 22 4.3 Calibration of the “final” model 24 4.4 The demand analysis through the final Multinomial Logit model 25 5 The analysis of interaction between the demand and socioeconomic attributes 31 5.1 Methodology 31 5.2 Application of Mixed Logit models to the demand 31 5.3 Analysis of the interactions between demand and socioeconomic attributes through Mixed Logit models 32 5.4 Mixed Logit model and interaction between age and the demand for the CTS 38 5.5 Demand analysis with Mixed Logit model 39 6 Final analyses and conclusions 45 6.1 Comparison between the results of the analyses 45 6.2 Conclusions 48 6.3 Answers to the research questions and future developments 52

The European commission

Face Age Progression (FAP) refers to synthesizing face images while simulating ageing effects, thus enabling predicting the future appearance of an individual. The generation of age-progressed face images brings benefits for various applications, ranging from face recognition systems to forensic investigations and digital entertainment. In particular, the recent success achieved with deep generative networks significantly leveraged the quality of age-synthesized face images in terms of visual fidelity, ageing accuracy and identity preservation. However, the high number of contributions in recent years requires systematically structuring new findings and ideas to identify a common taxonomy, accelerate future research and reduce redundancy. Therefore, we present a comparative analysis of recent deep learning based face age progression methods for both adult and child-based face ageing, broken down into three high-level concepts: translation-based, condition-based, and sequence-based FAP. Further, we offer a comprehensive summary of the most common performance evaluation techniques, cross-age datasets, and open challenges to steer future research in the right direction.

/pdf/deep-face-age-progression-a-survey-2f5plb567q.pdf

Deep Face Age Progression: A Survey

Applicability of the face recognition for smartphone-based authentication applications is increasing for different domains such as banking and e-commerce. The unsupervised data capture of face characteristics in biometric applications on smartphones presents the vulnerability to attack the systems using artefact samples. The threat of presentation attacks (a.k.a spoofing attacks) need to be handled to enhance the security of the biometric system. In this work, we present a new approach of using the raw sensor data. We first obtain the residual image corresponding to noise by subtracting the median filtered version of raw data and then computing simple energy value to detect the artefact based presentations. The presented approach uses simple threshold and thereby overcomes the need for learning complex classifiers which are challenging to work on unseen attacks. The proposed method is evaluated using a newly collected database of 390 live presentation attempts of face characteristics and 1530 attack presentations consisting of electronic screen attacks and printed attacks on the iPhone 6S smartphone. Significantly lower average classification error (

Presentation Attack Detection in Face Biometric Systems Using Raw Sensor Data from Smartphones

/pdf/the-watchlist-imbalance-effect-in-biometric-face-45m270i5uy.pdf

The Watchlist Imbalance Effect in Biometric Face Identification: Comparing Theoretical Estimates and Empiric Measurements

Iris biometrics is considered as the unique and accurate biometric characteristics that are suited for large scale applications such as India's AADHAR, CANPASS, and many other national ID programs. However, the accuracy of the iris recognition is observed to degrade when eye (or iris) is affected by the diseases. Among many other eye diseases, cataract results in a cloud formation on the eye lens and is a potential problem, especially in the developing countries. In this paper, we present a preliminary study on 84 data subjects to reveal the effect of cataract on iris recognition performance. We investigate three different scenarios, which involve: (1) Enrolment and recognition of affected eyes (pre-operated eye) (2) Enrolement and recognition of operated eyes (post-operated eye) (3) Enrolment with affected eyes and recognition with operated eyes. Extensive experiments are carried out using five different academic and commercial iris recognition methods to get complete insight on the impact of cataract on the recognition performance. Results obtained on our database indicate the degraded performance in verification of the cataract operated eye.

Influence of cataract surgery on iris recognition: A preliminary study

We investigate ear recognition systems for severe signal degradation of ear images in order to assess the impact on biometric performance of diverse well-established feature extraction algorithms. Various intensities of signal degradation, i.e. out-of-focus blur and thermal noise, are simulated in order to construct realistic acquisition scenarios. Experimental evaluations, which are carried out on a comprehensive database comprising more than 2,000 ear images, point out the effects of severe signal degradation on ear recognition performance using appearance features.

/pdf/impact-of-severe-signal-degradation-on-ear-recognition-ufol2ozu47.pdf

Christoph Busch

Papers

Deep Face Age Progression: A Survey

Presentation Attack Detection in Face Biometric Systems Using Raw Sensor Data from Smartphones

The Watchlist Imbalance Effect in Biometric Face Identification: Comparing Theoretical Estimates and Empiric Measurements

Influence of cataract surgery on iris recognition: A preliminary study

Impact of severe signal degradation on ear recognition performance