Semi-supervised and unsupervised kernel-based novelty detection with application to remote sensing images
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
Domain language model adaptation consists in re-estimating probabilities of a baseline LM in order to better match the specifics of a given broad topic of interest. To do so, a common strategy is to retrieve adaptation texts from the Web based on a given d ...
Training Support Vector Machines (SVMs) to predict drugs concentrations is often difficult because of the high level of noise in the training data, due to various kinds of measurement errors. We apply RANdom SAmple Consensus (RANSAC) algorithm in this pape ...
Extracting linear structures, such as blood vessels or dendrites, from images is crucial in many medical imagery applications, and many handcrafted features have been proposed to solve this problem. However, such features rely on assumptions that are never ...
Conventional linear subspace learning methods like principal component analysis (PCA), linear discriminant analysis (LDA) derive subspaces from the whole data set. These approaches have limitations in the sense that they are linear while the data distribut ...
Institute of Electrical and Electronics Engineers2011
White matter hyperintensities (WMH) are the focus of intensive research and have been linked to cognitive impairment and depression in the elderly. Cumbersome manual outlining procedures make research on WMH labour intensive and prone to subjective bias. T ...
Fully automated machine learning methods based on structural magnetic resonance imaging data can assist radiologists in the diagnosis of Alzheimer's disease (AD). These algorithms require large data sets to learn the separation of subjects with and without ...
A common trend in machine learning and pattern classification research is the exploitation of massive amounts of information in order to achieve an increase in performance. In particular, learning from huge collections of data obtained from the web, and us ...
Machine Learning techniques play an increasingly vital role in the analysis of Biomedical imagery, as in all other areas of Computer Vision. However, in this specific context, they suffer from the fact that experimental conditions and protocols change ofte ...
Domain language model adaptation consists in re-estimating probabilities of a baseline LM in order to better match the specifics of a given broad topic of interest. To do so, a common strategy is to retrieve adaptation texts from the Web based on a given d ...
A common trend in machine learning and pattern classification research is the exploitation of massive amounts of information in order to achieve an increase in performance. In particular, learning from huge collections of data obtained from the web, and us ...