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

In security systems the risk assessment in the sense of common criteria testing is a very relevant topic; this requires quantifying the attack potential in terms of the expertise of the attacker, his knowledge about the target and access to equipment. Contrary to those attacks, the recently revealed morphing attacks against Face Recognition Systems (FRSs) can not be assessed by any of the above criteria. But not all morphing techniques pose the same risk for an operational face recognition system. This paper introduces with the Morphing Attack Potential (MAP) a consistent methodology, that can quantify the risk, which a certain morphing attack creates.

Morphing Attack Potential

Convolutional Neural Networks (CNNs) have shown promising results on Single Image Super-Resolution (SISR) task. A pair of Low-Resolution (LR) and High-Resolution (HR) images are typically used in the CNN models to train them to super-resolve LR images in a fully supervised manner. Owing to non-availability of true LR-HR pairs, the LR images are generally synthesized from HR data by applying synthetic degradation such as bicubic downsampling. Such networks under-perform when used on real-world data where degradation is different from the synthetically generated LR image. As obtaining true LR-HR pair is a tedious and resource (time and effort) consuming task, we propose a new approach and architecture to super-resolve the real-world LR images in an unsupervised manner by using a Generative Adversarial Network (GAN) framework with Variational Auto-Encoder (VAE). Along with a new network architecture, we also introduce a novel loss metric based on no-reference quality scores of SR images to improve the perceptual fidelity of the SR images. Through the experiments on NTIRE-2020 Real-World SR Challenge dataset, we demonstrate the superiority of the proposed approach over the other competing state-of-the-art methods.

Unsupervised Real-World Super-resolution Using Variational Auto-encoder and Generative Adversarial Network.

Periocular biometric verification on the smartphone is gaining more popularity with the increasing functionality and accessibility of the services offered using smartphones. However accurate periocular verification requires especially on the smartphone to address several challenges due to the uncontrolled image capturing conditions. In this paper, we present a novel scheme for accurate periocular recognition based on a comparative score fusion. Given the periocular image, the proposed method will first perform the pre-processing to enhance the quality of the captured periocular image. The enhanced periocular image is processed further to extract texture features using Log-Gabor filters. In the next step, we train two different classifiers such as deep autoencoder and Relaxed Collaborative Representation (RCR) on the texture features. Then, given the probe periocular image, we obtain the corresponding comparator scores for each of these comparators that are fused using weighted sum rule to perform the verification. Extensive experiments are carried out on a large-scale smartphone based periocular database comprised of 550 subjects recorded in three different scenarios using three different smartphones. In depth analysis on the benchmark of the proposed scheme with five different state-of-the-art schemes demonstrates the outstanding performance of the proposed scheme with a consistent GMR of about 99% at FMR = 10−3.

On comparison score fusion of deep autoencoders and relaxed collaborative representation for smartphone based accurate periocular verification

Automatic Border Control (ABC) systems based on face recognition are widely deployed in a border control scenarios. The efficiency of a ABC system depends on the early recognition of the capture subject as soon as he/she appears in the vicinity of the camera. However, due to various factors, including the change in illumination conditions, it is often challenging to capture a good quality face sample to facilitate the speedy biometric recognition with the ABC systems. In this paper, we propose a novel super resolution scheme to enhance the resolution of the captured face image. The proposed method is based on a weighted fusion of high frequency sub-band images obtained using Discrete Wavelet Transform (DWT) and Stationary Wavelet Transform (SWT). The weights are computed and assigned to the corresponding sub-band images of DWT and SWT by measuring both correlation and energy. Then, weighted sub-band images are fused using the sum rule. Finally, all these sub-bands are combined to generate a new resolution enhanced image using Inverse Discrete Wavelet Transform (IDWT). Extensive experiments are carried out using a semi-public ABC database that is comprised of 61 subjects. The database was captured in three different lighting conditions. Further, we also compare the performance of the proposed Super Resolution (SR) scheme with three well established state-of-the-art schemes. The experimental results have indicated that the proposed SR scheme can effectively improve the face recognition component of the ABC system even with low quality face samples.

Face image resolution enhancement based on weighted fusion of wavelet decomposition

Biometric gait recognition is a well suited method for authentication on mobile devices as it is unobtrusive and concurrent. Hence, in contrast to PIN authentication it is no extra-effort for the user. The characteristic gait of a subject can be recorded using accelerometers which are nowadays already contained in many mobile devices. From this data biometric feature vectors can be extracted and stored as reference data on the device. Only if the user is not recognized by his walk an active authentication via PIN is necessary. As the number of attacks on mobile devices increases it cannot be assumed that the data stored on the device is under constant control of the subject. Therefore, template protection techniques should be applied to secure biometric data. As biometric gait recognition is a new field of research no specific template protection methods have been developed so far. This paper describes a new method for securing biometric gait features based on histograms and using the earth mover’s distance for comparison. The method is tested with gait data of 48 subjects recorded using a mobile phone and the results are compared to the ones obtained without template protection.

Christoph Busch

Papers

Morphing Attack Potential

Unsupervised Real-World Super-resolution Using Variational Auto-encoder and Generative Adversarial Network.

On comparison score fusion of deep autoencoders and relaxed collaborative representation for smartphone based accurate periocular verification

Face image resolution enhancement based on weighted fusion of wavelet decomposition

Template Protection for Biometric Gait Data.