—We present a computer-aided detection (CAD) system for computed tomography colonography that orders the polyps according to clinical relevance. The CAD system consists of two st...
Vincent Frans van Ravesteijn, Cees van Wijk, Frans...
—Recent years have witnessed the deployments of wireless sensor networks in a class of mission-critical applications such as object detection and tracking. These applications oft...
Botnets have become the most powerful tool for attackers to victimize countless users across cyberspace. Previous work on botnet detection has mainly focused on identifying infecte...
Jose Andre Morales, Erhan J. Kartaltepe, Shouhuai ...
Lymph node detection and measurement is a difficult and important part of cancer treatment. In this paper we present a robust and effective learning-based method for the automatic...
An important task in exploration of data about phenomena and processes that develop over time is detection of significant changes that happened to the studied phenomenon. Our rese...
Gennady L. Andrienko, Natalia V. Andrienko, Martin...
This paper describes a method to minimize the immense training time of the conventional Adaboost learning algorithm in object detection by reducing the sampling area. A new algorit...
Florian Baumann, Katharina Ernst, Arne Ehlers, Bod...
Abstract—In cognitive radio networks (CRNs), detecting smallscale primary devices—such as wireless microphones (WMs)— is a challenging, but very important, problem that has n...
Recently, accidents such that seniors fall down from the bed in care facilities or hospitals are increased. To prevent these accidents, we have developed an awakening detection sys...
— This work addresses the task of designing the optimal survey route that an autonomous underwater vehicle (AUV) should take in mine countermeasures (MCM) operations. It is assum...
—We apply large deviations theory to study asymptotic performance of running consensus distributed detection in sensor networks. Running consensus is a stochastic approximation t...