… the acoustic event detection (AED) to improve the detection accuracy of acoustic events.
Acoustic … This paper studies the isolated acoustic event detection and proposes a novel concept …

… an approach based on random forest regression. Furthermore, event localization in time can
be … More importantly, random forest classification supports probability output which we will …

… To apply deep random forest to polyphonic sound event detection, we use OvR … deep random
forest per event class. We trained 7 deep random forest, of 6 are trained for the sound event…

… random forest regression based acoustic event detection (… -world acoustic events, an acoustic
event detection system is … consist of highly variable acoustic events. Experimental results …

The variety of event categories and event boundary information have resulted in limited
success for acoustic event detection systems. To deal with this, we propose to utilize the long …

… Random Forest Method for Traffic Event Detection This section adopts Random Forest (RF)
for traffic event detection. … and experiments, scholars have proved the Random Forest. …

… detectors throughout the city, but event contexts were only included at detectors on routes
into and out of the event … , a novel random forest incident detection algorithm which aimed to …

… In this paper we focus on the adoption of random forest model to detect and extract from a
large set of tweets main features and related rules of a sudden critical event. After a number of …

… the multivariate regression forests in Section 2 and our event detection and localization system
… We adopt random forest classification [14] to train the classifiers to take advantage of its …

… random forest could grow deep and tend to learn highly irregular patterns of spatiotemporal
events … 2.1, we will discuss several motion symbol detection methods. In Sect. 2.2, we will …