This paper presents a novel approach of applying both positive selection and negative selection to supervised learning for anomaly detection. It first learns the patterns of the n...
During the last decade, anomaly detection has attracted the attention of many researchers to overcome the weakness of signature-based IDSs in detecting novel attacks. However, hav...
Mahbod Tavallaee, Wei Lu, Shah Arif Iqbal, Ali A. ...
We propose a multi-target tracking (MTT) algorithm in a sequential Bayesian framework that computes cell velocities from video microscopy. Unlike the traditional tracking methods,...
An automated method for left ventricle detection in MR cardiac images is presented. Ventricle detection is the rst step in a fully automated segmentation system used to compute vo...
Nicolae Duta, Anil K. Jain, Marie-Pierre Dubuisson...
Lymph nodes have high clinical relevance but detection is challenging as they are hard to see due to low contrast and irregular shape. In this paper, a method for fully automatic ...
Johannes Feulner, Kevin Zhou, Martin Huber, Joachi...