Interpretazione in una logica n-dimensionale di Metafisica 4,4

Il Principio di non contraddizione (PNC) così come tradizionalmente inteso sembra minare alla base la possibilità di un'alterità « assoluta », di un'alterità, cioè che non sia in nessun modo riconducibile ad un'ipseità che la conosca. [...]

Infinito, conoscenza e trascendenza

Quello che mi propongo in queste pagine è una breve analisi del debito che Levinas ha nei confronti di Cartesio per quanto concerne l'elaborazione del concetto di infinito in « Totalità e infinito ». [...]

Le livrel et le format ePub

Il ne serait pas possible de tracer un panorama complet des enjeux de l’édition numérique sans parler des formats qui tentent de reproduire le mode typique de circulation des contenus papier — le livre — en l’adaptant au support numérique. C’est ce que l’on appelle « livre électronique » ou « livrel » (eBook en anglais). Il ne faut pas confondre le livre électronique avec la liseuse qui est le support de lecture. Le livre électronique est un fichier, formaté selon des standards déterminés. Bien évidemment, ces formats ne sont pas stables et changent très rapidement. Aujourd’hui, le standard ouvert de référence est l’ePub. Ce chapitre essaie d’en donner une description.

La littérature numérique, existe-t-elle?

This article attempts to analyze the definition of "electronic literature" as given by the Electronic Literature Organization and to understand the relationship between electronic literature and digital literature. The thesis defended here is that this change of adjective hides a change in the theoretical status of the object that it attempts to define. The definition of electronic literature once concentrated on the tools used in the production of literary works and the critical analysis concentrating on the objects produced with the aid of new technologies. The move to the adjective "digital" marks a change in perception: now, from this perspective, the challenge is no longer to study works produced thanks to computers, but to understand the new status of literature in the age of the digital. To demonstrate this thesis, the article proposes to analyze one recent literary example: the 1984 trilogy by Eric Plamondon.

Considerazioni generali sul concetto di « corpo »

Il concetto di “corpo” è evidentemente alla base della pratica medica. Dalla definizione che si sceglie di dare a questo concetto dipende l’idea stessa di medicina e di terapia. È per questo che una riflessione preliminare su che cosa sia il corpo è necessaria per guidare e impostare qualsiasi azione dell’operatore sanitario. [...]

Riflessioni filosofiche sul metodo Rességuier

Il metodo Rességuier presenta degli aspetti di grande interesse teorico che implicano un ripensamento dei concetti cardine su cui si basa l’idea di cura e di terapia. Con questo scritto intendo analizzarli per sommi capi in modo tale da approfondire le basi filosofiche su cui tale metodo sembra riposare. Questa analisi ha come obiettivo da una parte un approfondimento del metodo che porti ad una migliore comprensione della sua pratica, dall’altra una riflessione che, partendo dal metodo stesso, vada a interrogarsi sulle idee filosofiche che sono da sempre state alla base della medicina. [...]

A Note on Object Class Representation and Categorical Perception

We present a novel scheme ("Categorical Basis Functions", CBF) for object class representation in the brain and contrast it to the "Chorus of Prototypes" scheme recently proposed by Edelman. The power and flexibility of CBF is demonstrated in two examples. CBF is then applied to investigate the phenomenon of Categorical Perception, in particular the finding by Bulthoff et al. (1998) of categorization of faces by gender without corresponding Categorical Perception. Here, CBF makes predictions that can be tested in a psychophysical experiment. Finally, experiments are suggested to further test CBF.

Learning-Based Approach to Real Time Tracking and Analysis of Faces

This paper describes a trainable system capable of tracking faces and facialsfeatures like eyes and nostrils and estimating basic mouth features such as sdegrees of openness and smile in real time. In developing this system, we have addressed the twin issues of image representation and algorithms for learning. We have used the invariance properties of image representations based on Haar wavelets to robustly capture various facial features. Similarly, unlike previous approaches this system is entirely trained using examples and does not rely on a priori (hand-crafted) models of facial features based on optical flow or facial musculature. The system works in several stages that begin with face detection, followed by localization of facial features and estimation of mouth parameters. Each of these stages is formulated as a problem in supervised learning from examples. We apply the new and robust technique of support vector machines (SVM) for classification in the stage of skin segmentation, face detection and eye detection. Estimation of mouth parameters is modeled as a regression from a sparse subset of coefficients (basis functions) of an overcomplete dictionary of Haar wavelets.

A Trainable Object Detection System: Car Detection in Static Images

This paper describes a general, trainable architecture for object detection that has previously been applied to face and peoplesdetection with a new application to car detection in static images. Our technique is a learning based approach that uses a set of labeled training data from which an implicit model of an object class -- here, cars -- is learned. Instead of pixel representations that may be noisy and therefore not provide a compact representation for learning, our training images are transformed from pixel space to that of Haar wavelets that respond to local, oriented, multiscale intensity differences. These feature vectors are then used to train a support vector machine classifier. The detection of cars in images is an important step in applications such as traffic monitoring, driver assistance systems, and surveillance, among others. We show several examples of car detection on out-of-sample images and show an ROC curve that highlights the performance of our system.

Information Dissemination and Aggregation in Asset Markets with Simple Intelligent Traders

Various studies of asset markets have shown that traders are capable of learning and transmitting information through prices in many situations. In this paper we replace human traders with intelligent software agents in a series of simulated markets. Using these simple learning agents, we are able to replicate several features of the experiments with human subjects, regarding (1) dissemination of information from informed to uninformed traders, and (2) aggregation of information spread over different traders.

Image-Based View Synthesis

We present a new method for rendering novel images of flexible 3D objects from a small number of example images in correspondence. The strength of the method is the ability to synthesize images whose viewing position is significantly far away from the viewing cone of the example images ("view extrapolation"), yet without ever modeling the 3D structure of the scene. The method relies on synthesizing a chain of "trilinear tensors" that governs the warping function from the example images to the novel image, together with a multi-dimensional interpolation function that synthesizes the non-rigid motions of the viewed object from the virtual camera position. We show that two closely spaced example images alone are sufficient in practice to synthesize a significant viewing cone, thus demonstrating the ability of representing an object by a relatively small number of model images --- for the purpose of cheap and fast viewers that can run on standard hardware.

Model-Based Matching by Linear Combinations of Prototypes

We describe a method for modeling object classes (such as faces) using 2D example images and an algorithm for matching a model to a novel image. The object class models are "learned'' from example images that we call prototypes. In addition to the images, the pixelwise correspondences between a reference prototype and each of the other prototypes must also be provided. Thus a model consists of a linear combination of prototypical shapes and textures. A stochastic gradient descent algorithm is used to match a model to a novel image by minimizing the error between the model and the novel image. Example models are shown as well as example matches to novel images. The robustness of the matching algorithm is also evaluated. The technique can be used for a number of applications including the computation of correspondence between novel images of a certain known class, object recognition, image synthesis and image compression.

Model-Based Matching of Line Drawings by Linear Combinations of Prototypes

We describe a technique for finding pixelwise correspondences between two images by using models of objects of the same class to guide the search. The object models are 'learned' from example images (also called prototypes) of an object class. The models consist of a linear combination ofsprototypes. The flow fields giving pixelwise correspondences between a base prototype and each of the other prototypes must be given. A novel image of an object of the same class is matched to a model by minimizing an error between the novel image and the current guess for the closest modelsimage. Currently, the algorithm applies to line drawings of objects. An extension to real grey level images is discussed.

Example Based Learning for View-Based Human Face Detection

We present an example-based learning approach for locating vertical frontal views of human faces in complex scenes. The technique models the distribution of human face patterns by means of a few view-based "face'' and "non-face'' prototype clusters. At each image location, the local pattern is matched against the distribution-based model, and a trained classifier determines, based on the local difference measurements, whether or not a human face exists at the current image location. We provide an analysis that helps identify the critical components of our system.

View-Based Strategies for 3D Object Recognition

A persistent issue of debate in the area of 3D object recognition concerns the nature of the experientially acquired object models in the primate visual system. One prominent proposal in this regard has expounded the use of object centered models, such as representations of the objects' 3D structures in a coordinate frame independent of the viewing parameters [Marr and Nishihara, 1978]. In contrast to this is another proposal which suggests that the viewing parameters encountered during the learning phase might be inextricably linked to subsequent performance on a recognition task [Tarr and Pinker, 1989; Poggio and Edelman, 1990]. The 'object model', according to this idea, is simply a collection of the sample views encountered during training. Given that object centered recognition strategies have the attractive feature of leading to viewpoint independence, they have garnered much of the research effort in the field of computational vision. Furthermore, since human recognition performance seems remarkably robust in the face of imaging variations [Ellis et al., 1989], it has often been implicitly assumed that the visual system employs an object centered strategy. In the present study we examine this assumption more closely. Our experimental results with a class of novel 3D structures strongly suggest the use of a view-based strategy by the human visual system even when it has the opportunity of constructing and using object-centered models. In fact, for our chosen class of objects, the results seem to support a stronger claim: 3D object recognition is 2D view-based.