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Premature babies are not fully equipped to deal with the outside world. Their immature bodies make them highly at risk to a large number of physiological complications. Therefore, while they are still immature, premature babies are taken care of in neonato ...
In this paper we present a new method to enhance object detection by removing false alarms and merging multiple detections in a principled way with few parameters. The method models the output of an object classiï¬er which we consider as the context. A hie ...
Activation of most major innate immune signalling cascades relies on the detection of microorganisms or their associated danger signals by host pattern recognition molecules. A flurry of recent studies has now uncovered a role for host translation inhibiti ...
Monitoring traffic events in computer network has become a critical task for operators to maintain an accurate view of a network's condition, to detect emerging security threats, and to safeguard the availability of resources. Conditions detrimental to a n ...
Real-data testing results of a real-time nonlinear freeway traffic state estimator are presented with a particular focus on its adaptive features. The pursued general approach to the real-time adaptive estimation of complete traffic state in freeway stretc ...
Machine-learning based classification techniques have been shown to be effective at detecting objects in complex scenes. However, the final results are often obtained from the alarms produced by the classifiers through a post-processing which typically rel ...
Since privacy issues are becoming important with growth of the video surveillance, many tools are proposed for protection of personal privacy in the video. However, little is understood regarding the effectiveness of such tools and their effect on the unde ...
This paper presents a system for keyword detection in spontaneous speech. Keywords are predefined through a set of acoustic examples provided by the users. Keyword detection proceeds in two steps: keyword searching and verification. To address the problem ...
This paper presents a method for the automated detection of dropped objects in surveillance scenarios, which is a very important task for abandoned object detection. Our method works in single views and exploits prior information of the scene, such as geom ...
Machine-learning based classification techniques have been shown to be effective at detecting objects in com- plex scenes. However, the final results are often obtained from the alarms produced by the classifiers through a post-processing which typically r ...