Binary segmentation, a problem of extracting foreground objects from the background, often arises in medical imaging and document processing. Popular existing solutions include Ex...
Anomaly detection in multivariate time series is an important data mining task with applications to ecosystem modeling, network traffic monitoring, medical diagnosis, and other d...
Christopher Potter, Haibin Cheng, Pang-Ning Tan, S...
This paper makes a rereading of two successful image segmentation approaches, the fuzzy connectedness (FC) and the watershed (WS) approaches, by analyzing both by means of the Ima...
This paper presents a novel non-rigid object localization and segmentation algorithm using an eigenspace representation. Previous approaches to eigenspace methods for object track...
We present a new variational level-set-based segmentation
formulation that uses both shape and intensity prior information
learned from a training set. By applying Bayes’
rule...