Evaluation of Biometric Systems

International audienceBiometrics is considered as a promising solution among traditional methods based on "what we own" (such as a key) or "what we know" (such as a password). It is based on "what we are" and "how we behave". Few people know that biometrics have been used for ages for identification or signature purposes. In 1928 for example, fingerprints were used for women clerical employees of Los Angeles police department as depicted in Figure 1. Fingerprints were also already used as a signature for commercial exchanges in Babylon (-3000 before JC). Alphonse Bertillon proposed in 1879 to use anthropometric information for police investigation. Nowadays, all police forces in the world use this kind of information to resolve crimes. The first prototypes of terminals providing an automatic processing of the voice and digital fingerprints have been defined in the middle of the years 1970. Nowadays, biometric authentication systems have many applications [1]: border control, e-commerce, etc. The main benefits of this technology are to provide a better security, and to facilitate the authentication process for a user. Also, it is usually difficult to copy the biometric characteristics of an individual than most of other authentication methods such as passwords. Despite the obvious advantages of biometric systems, their proliferation was not as much as attended. The main drawback is the uncertainty of the verification result. By contrast to password checking, the verification of biometric raw data is subject to errors and represented by a similarity percentage (100% is never reached). Others drawbacks related to vulnerabilities and usability issues exist. In addition, in order to be used in an industrial context, the quality of a biometric system must be precisely quantified. We need a reliable evaluation methodology in order to put into obviousness the benefit of a new biometric system. Moreover, many questions remain: Shall we be confident in this technology? What kind of biometric modalities can be used? What are the trends in this domain? The objective of this chapter is to answer these questions, by presenting an evaluation methodology of biometric systems

Tabu search model selection for SVM

International audienceA model selection method based on tabu search is proposed to build support vector machines (binary decision functions) of reduced complexity and efficient generalization. The aim is to build a fast and efficient support vector machines classifier. A criterion is defined to evaluate the decision function quality which blends recognition rate and the complexity of a binary decision functions together. The selection of the simplification level by vector quantization, of a feature subset and of support vector machines hyperparameters are performed by tabu search method to optimize the defined decision function quality criterion in order to find a good sub-optimal model on tractable times

Construction du dictionnaire par coopération de modèles statistiques et perceptuels pour la quantification vectorielle d'images couleur

· La qualité des schémas de compression des images numériques couleur est fortement limitée par l'absence de coopération entre une approche statistique et une approche perceptuelle; ces deux domaines étant très souvent « ignorés » l'un par l'autre. Cependant une coopération entre ces deux approches permettrait un net gain de qualité des images resconstruites. Dans le contexte de la compression des images couleur par quantification vectorielle, nous définissons un algorithme de construction perceptuellement amélioré du dictionnaire basé l'exploitation conjointe des redondances statistiques et perceptuelles des images. Les résultats obtenus à l'aide de mesures de fidélité et psychophysiques permettent de conclure à un gain substantiel vis-à vis du rendu des couleurs et des contours, pour une complexité et un taux de compression comparables à ceux de l'algorithme LBG

Optimisation du dictionnaire pour la quantification Vectorielle d'images couleur

Lors de la compression d'images couleur par la technique de la Quantification Vectorielle (QV), il est primordial d'obtenir un dictionnaire représentant au mieux les images. Une des techniques la plus couramment utilisée pour cette étape est la méthode LBG. Or cette solution ne permet pas de prendre en compte la totalité de la répartition spatial du nuage couleur associé à l'image. Pour remédier à cet handicap, nous avons introduit une étape dans l'algorithme LBG basée sur l'algorithme du Max-Min. Les résultats obtenus à partir de mesures objectives et psychophysiques ont permis de conclure à la supériorité de notre méthode même si le temps de calcul est légèrement plus important

Une métrique psychovisuelle d'évaluation de la qualité des images couleur intégrant les effets de masquage inter-canal

- Tout traitement appliqué sur des images numériques doit, au final, être validé par un processus de qualité. Dans le cadre de la compression des images, ce processus repose sur la mesure de la qualité de l'image reconstruite. Or, le recours à des études subjectives est très coûteux car fastidieux à mettre en oeuvre. Dès lors, de nombreuses métriques de qualité sont apparues avec pour principal objectif la corrélation avec le jugement humain. Dans ce papier, une métrique psychovisuelle de la qualité basée sur une décomposition en ondelettes et sur une mesure des effets de masquage intra et inter-bande est développée. Une étude des performances est réalisée en terme de corrélation et de robustesse au type d'images

Recommending Podcasts for Cold-Start Users Based on Music Listening and Taste

Recommender systems are increasingly used to predict and serve content that aligns with user taste, yet the task of matching new users with relevant content remains a challenge. We consider podcasting to be an emerging medium with rapid growth in adoption, and discuss challenges that arise when applying traditional recommendation approaches to address the cold-start problem. Using music consumption behavior, we examine two main techniques in inferring Spotify users preferences over more than 200k podcasts. Our results show significant improvements in consumption of up to 50\% for both offline and online experiments. We provide extensive analysis on model performance and examine the degree to which music data as an input source introduces bias in recommendations.Comment: SIGIR 202

From Understanding Cellular Function to Novel Drug Discovery: The Role of Planar Patch-Clamp Array Chip Technology

All excitable cell functions rely upon ion channels that are embedded in their plasma membrane. Perturbations of ion channel structure or function result in pathologies ranging from cardiac dysfunction to neurodegenerative disorders. Consequently, to understand the functions of excitable cells and to remedy their pathophysiology, it is important to understand the ion channel functions under various experimental conditions – including exposure to novel drug targets. Glass pipette patch-clamp is the state of the art technique to monitor the intrinsic and synaptic properties of neurons. However, this technique is labor intensive and has low data throughput. Planar patch-clamp chips, integrated into automated systems, offer high throughputs but are limited to isolated cells from suspensions, thus limiting their use in modeling physiological function. These chips are therefore not most suitable for studies involving neuronal communication. Multielectrode arrays (MEAs), in contrast, have the ability to monitor network activity by measuring local field potentials from multiple extracellular sites, but specific ion channel activity is challenging to extract from these multiplexed signals. Here we describe a novel planar patch-clamp chip technology that enables the simultaneous high-resolution electrophysiological interrogation of individual neurons at multiple sites in synaptically connected neuronal networks, thereby combining the advantages of MEA and patch-clamp techniques. Each neuron can be probed through an aperture that connects to a dedicated subterranean microfluidic channel. Neurons growing in networks are aligned to the apertures by physisorbed or chemisorbed chemical cues. In this review, we describe the design and fabrication process of these chips, approaches to chemical patterning for cell placement, and present physiological data from cultured neuronal cells

T Follicular Helper Cells in Autoimmune Disorders

T follicular helper (Tfh) cells are a distinct subset of CD4+ T lymphocytes, specialized in B cell help and in regulation of antibody responses. They are required for the generation of germinal center reactions, where selection of high affinity antibody producing B cells and development of memory B cells occur. Owing to the fundamental role of Tfh cells in adaptive immunity, the stringent control of their production and function is critically important, both for the induction of an optimal humoral response against thymus-dependent antigens but also for the prevention of self-reactivity. Indeed, deregulation of Tfh activities can contribute to a pathogenic autoantibody production and can play an important role in the promotion of autoimmune diseases. In the present review, we briefly introduce the molecular factors involved in Tfh cell formation in the context of a normal immune response, as well as markers associated with their identification (transcription factor, surface marker expression, and cytokine production). We then consider in detail the role of Tfh cells in the pathogenesis of a broad range of autoimmune diseases, with a special focus on systemic lupus erythematosus and rheumatoid arthritis, as well as on the other autoimmune/inflammatory disorders. We summarize the observed alterations in Tfh numbers, activation state, and circulating subset distribution during autoimmune and some other inflammatory disorders. In addition, central role of interleukin-21, major cytokine produced by Tfh cells, is discussed, as well as the involvement of follicular regulatory T cells, which share characteristics with both Tfh and regulatory T cells