Object and Scene Classification: what does a Supervised Approach Provide us?

Given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurrences to perform a scene classification (e.g. beach scene, mountain scene). We achieve this by using a supervised learning algorithm able to learn with few images to facilitate the user task. We use a probabilistic model to recognise the objects and further we classify the scene based on their object occurrences. Experimental results are shown and evaluated to prove the validity of our proposal. Object recognition performance is compared to the approaches of He et al. (2004) and Marti et al. (2001) using their own datasets. Furthermore an unsupervised method is implemented in order to evaluate the advantages and disadvantages of our supervised classification approach versus an unsupervised one

A new approach to the classification of mammographic masses and normal breast tissue

A new approach to mammographic mass detection is presented in this paper. Although different algorithms have been proposed for such a task, most of them are application dependent. In contrast, our approach makes use of a kindred topic in computer vision adapted to our particular problem. In this sense, we translate the eigenfaces approach for face detection/classification problems to a mass detection. Two different databases were used to show the robustness of the approach. The first one consisted on a set of 160 regions of interest (RoIs) extracted from the MIAS database, being 40 of them with confirmed masses and the rest normal tissue. The second set of RoIs was extracted from the DDSM database, and contained 196 RoIs containing masses and 392 with normal, but suspicious regions. Initial results demonstrate the feasibility of using such approach with performances comparable to other algorithms, with the advantage of being a more general, simple and cost-effective approach

Organització de la producció: problemes [versió html]

Aquest manual recull un conjunt de problemes, alguns resolts i d’altres no, que complementen l’aprenentatge en l’àmbit de l’organització de la producció. El seu enfocament està dirigit a estudis universitaris, i pretén ser un complement dels manuals ja existents, mitjançant la resolució dels problemes més habituals a resoldre en l’Organització de la Producció

Organització de la producció: problemes [versió comprimida]

Aquest manual recull un conjunt de problemes, alguns resolts i d’altres no, que complementen l’aprenentatge en l’àmbit de l’organització de la producció. El seu enfocament està dirigit a estudis universitaris, i pretén ser un complement dels manuals ja existents, mitjançant la resolució dels problemes més habituals a resoldre en l’Organització de la Producció