Eigenmaps Of Dynamic Functional Connectivity: Voxel-Level Dominant Patterns Through Eigenvector Centrality
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.
The use of higher order autocorrelations as features for pattern classification has been usually restricted to second or third orders due to high computational costs. Since the autocorrelation space is a high dimensional space we are interested in reducing ...
Although many Offline Cursive Word Recognition systems are based on HMMs, no attention was ever paid, to our knowledge, to the fact that the feature vectors are typically not in the most suitable form for modeling. They are most of the time correlated and ...
Nonlocal means (NLM) is an effective denoising method that applies adaptive averaging based on similarity between neighborhoods in the image. An attractive way to both improve and speed-up NLM is by first performing a linear projection of the neighborhood. ...
A generalized expectation maximization (GEM) algorithm is used to retrieve the pose of a person from a monocular video sequence shot with a moving camera. After embedding the set of possible poses in a low dimensional space using principal component analys ...
We tested the hypothesis that common principles govern the production of the locomotor patterns for both straight-ahead and curved walking. Whole body movement recordings showed that continuous curved walking implies substantial, limb-specific changes in n ...
The central problem in the case of face detectors is to build a face class model. We present a method for face class modeling in the eigenfaces space using a large-margin classifier like SVM. Two main issues are addressed: what is the required number of ei ...
