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 Recognition Systems (FRS) are vulnerable to spoofing attacks (a.k.a presentation attacks), which can be carried out by presenting a printed photo (print-photo), displaying a photo (display-photo), or displaying a video (replay-video). The issue of presentation attacks can be alleviated by algorithms known as presentation attack detection (PAD) mechanisms. In this paper, we propose a novel framework based on Hierarchical Cosine/Spherical Linear Interpolation of deep learning feature vectors followed by training a Linear SVM for PAD Classification. The deep learning feature vectors are extracted from existing networks trained on the Imagenet dataset. Our proposed approach hierarchically interpolates the extracted feature vectors using Cosine/Spherically Linear Interpolation, followed by using a Linear SVM for classification, and sum-rule fusion for generating final scores. We show our results on cross-dataset PAD for the classifier trained on OULU P1 Dataset and tested on Replay Mobile Dataset. We compare it with the current state-of-the-art (SOTA) algorithms published in the literature and achieve considerably lower detection error-rate (D-EER). The extraction of features from pre-trained networks makes our approach simple to use, apart from it, giving highly accurate results, which are much better than current SOTA.

Hierarchical Interpolation of Imagenet Features for Cross-Dataset Presentation Attack Detection

Verschiedenste Algorithmen zum Markieren digitaler Daten wurden in den letzten Jahren veroffentlicht und entwickelt, um die Daten mit nicht wahrnehmbaren Kennzeichnern zu versehen. Unterschiede in den Algorithmen sind zum Teil nur marginal, oder sie unterscheiden sich in ihren Grundprinzipien. Eine objektive Bewertung existierender Algorithmen ist schwierig und kostenintensiv. Deshalb ist diese Bewertung sowohl fur kommerzielle als auch fur wissenschaftliche Organisationen nicht durchfuhrbar. Dadurch wird die Analyse neuer Ansatze verzogert. Ein automatisches Testverfahren ist somit nicht nur hilfreich, sondern auch notwendig, um objektive Vergleiche und Analysen zu ermoglichen, die fur die Verbesserung und die Neuentwicklung eine wichtige Grundlage darstellen. Wir beschreiben in diesem Beitrag die Unterschiede von Wasserzeichenalgorithmen und ihre Evaluierung am Beispiel verschiedener Angriffe. Desweiteren weisen wir auf die Notwendigkeit eines objektiven, nachvollziehbaren und allgemein anerkannten Testverfahrens hin. Aufgrund der Vielzahl existierender Algorithmen und Angriffe argumentieren wir fur die Notwendigkeit eines szenario-basierten Ansatzes.

/pdf/szenario-basierte-testverfahren-zur-zertifizierung-von-4hnxqou2ha.pdf

Szenario-basierte Testverfahren zur Zertifizierung von Wasserzeichen

Proceedings of the Second international conference on Web delivering of music

Lossy face image compression can degrade the image quality and the utility for the purpose of face recognition. This work investigates the effect of lossy image compression on a state-of-the-art face recognition model, and on multiple face image quality assessment models. The analysis is conducted over a range of specific image target sizes. Four compression types are considered, namely JPEG, JPEG 2000, downscaled PNG, and notably the new JPEG XL format. Frontal color images from the ColorFERET database were used in a Region Of Interest (ROI) variant and a portrait variant. We primarily conclude that JPEG XL allows for superior mean and worst case face recognition performance especially at lower target sizes, below approximately 5kB for the ROI variant, while there appears to be no critical advantage among the compression types at higher target sizes. Quality assessments from modern models correlate well overall with the compression effect on face recognition performance.

Effect of Lossy Compression Algorithms on Face Image Quality and Recognition

The workload of biometric identification in large fingerprint databases poses a challenging problem. Efficient schemes for biometric workload reduction are a topic of ongoing research. Some of the state-of-the-art approaches rely on triangles of minutia points generated by Delaunay triangulation, which are then used for indexing. In this paper, we investigate how quality estimation at the minutia level can improve the performance of such algorithms and hence the system workload. In order to reduce the number of spurious and missing minutiae, we analyse the impact of selecting minutiae points based on their qualities. This, in turn, can significantly distort the triangulation. In addition, we consider the usefulness of the average minutia quality as an additional criteria of the minutia triangles for indexing. Our results show that both strategies lead to a significant reduction in biometric workload compared to a baseline solution (i.e. exhaustive search) – down to 36% on average.

Christoph Busch

Papers

Hierarchical Interpolation of Imagenet Features for Cross-Dataset Presentation Attack Detection

Szenario-basierte Testverfahren zur Zertifizierung von Wasserzeichen

Proceedings of the Second international conference on Web delivering of music

Effect of Lossy Compression Algorithms on Face Image Quality and Recognition

Analysis of Minutiae Quality for Improved Workload Reduction in Fingerprint Identification