Is Sparsity Really Relevant for Image Classification?
Graph Chatbot
Chattez avec Graph Search
Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.
AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.
Visual information, in the form of images and video, comes from the interaction of light with objects. Illumination is a fundamental element of visual information. Detecting and interpreting illumination effects is part of our everyday life visual experien ...
Statistical pattern recognition occupies a central place in the general context of machine learning techniques, as it provides the theoretical insights and the practical means for solving a variety of problems ranging from character recognition to face rec ...
Humans have the ability to learn. Having seen an object we can recognise it later. We can do this because our nervous system uses an efficient and robust visual processing and capabilities to learn from sensory input. On the other hand, designing algorithm ...
A sparse classifier is guaranteed to generalize better than a denser one, given they perform identical on the training set. However, methods like Support Vector Machine, even if they produce relatively sparse models, are known to scale linearly as the numb ...
Using a low-level representation of images, like matching pursuit, we introduce a new way of describing objects through a general description using a translation, rotation, and isotropic scale invariant dictionary of basis functions. We then use this descr ...
This report describes the handwriting recognition demo on Linux and Windows. In the demo, we develop a prototype system of office management that provides pen-driven access to IDIAP people information, such as names, telephone numbers and nationalities thr ...
Recognition of handwritten text by computer can significantly reduce the cost of manual key entry in applications such as bank check processing, postal mail routing, census and poll form capture, medical documents, and many others. In this review, I will d ...
This report describes a system for handprinted character recognition. The goals of this work are to understand better the role of shape, shape representations, and shape similarity in character recognition, and to develop character recognition methods that ...
This paper describes a system that recognizes hand-printed digits. The system is based on optimal bounded error matching, a technique already in common use in general-purpose 2D and 3D visual object recognition systems in cluttered, noisy scenes. In this p ...
In this paper, I develop a higher-order statistical theory of matching models against images. The basic idea is not only to take into account {\em how much} of an object can be seen in the image, but also {\em what parts} of it are jointly present. I show ...
