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G2Face: High-Fidelity Reversible Face Anonymization via Generative and Geometric Priors

Reversible face anonymization, unlike traditional face pixelization, seeks to replace sensitive identity information in facial images with synthesized alternatives, preserving privacy without sacrificing image clarity. Traditional methods, such as …

Decision-based Evasion Attacks on Tree Ensemble Classifiers

Learning-based classifiers are found to be susceptible to adversarial examples. Recent studies suggested that ensemble classifiers tend to be more robust than single classifiers against evasion attacks. In this paper, we argue that this is not …

Cost-Sensitive Label Propagation for Semi-Supervised Face Recognition

In real-world applications, different kinds of learning and prediction errors are likely to incur different costs for the same system. Moreover, in practice, the cost label information is often available only for a few training samples. In a …

The PIT-trap—A “model-free” Bootstrap Procedure for Inference about Regression Models with Discrete, Multivariate Responses

Bootstrap methods are widely used in statistics, and bootstrapping of residuals can be especially useful in the regression context. However, difficulties are encountered extending residual resampling to regression settings where residuals are not …

Inference-based Similarity Search in Randomized Montgomery Domains for Privacy-preserving Biometric Identification

Similarity search is essential to many important applications and often involves searching at scale on high-dimensional data based on their similarity to a query. In biometric applications, recent vulnerability studies have shown that adversarial …

Learning Compact Binary Codes for Hash-Based Fingerprint Indexing

Compact binary codes can in general improve the speed of searches in large-scale applications. Although fingerprint retrieval was studied extensively with real-valued features, only few strategies are available for search in Hamming space. In this …

mvabund– an R package for model-based analysis of multivariate abundance data

Summary: 1. The mvabund package for R provides tools for model-based analysis of multivariate abundance data in ecology. 2. This includes methods for visualising data, fitting predictive models, checking model assumptions, as well as testing …

Distance-based multivariate analyses confound location and dispersion effects

Summary: 1. A critical property of count data is its mean–variance relationship, yet this is rarely considered inmultivariate analysis in ecology. 2. This study considers what is being implicitly assumed about the mean–variance relationship …

Global Ridge Orientation Modeling for Partial Fingerprint Identification

Identifying incomplete or partial fingerprints from a large fingerprint database remains a difficult challenge today. Existing studies on partial fingerprints focus on one-to-one matching using local ridge details. In this paper, we investigate the …

A Fingerprint Orientation Model Based on 2D Fourier Expansion (FOMFE) and Its Application to Singular-point Detection and Fingerprint Indexing

In this paper, we have proposed a fingerprint orientation model based on 2D Fourier expansions (FOMFE) in the phase plane. The FOMFE does not require prior knowledge of singular points (SPs). It is able to describe the overall ridge topology …