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Dahlem Center for Machine Learning and Robotics

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  • Wildfire Smoke Detection using Convolutional Neural Networks

Simon Philipp Hohberg:

Wildfire Smoke Detection using Convolutional Neural Networks

Kurzbeschreibung

Wildfires pose a threat to naure and human health especially in the age of global warming. Their early detection is key to an effective fighting, because once a wildfire reaches a certain size it can be hardly controlled.

Consequently, automated wildfire detection systems have been developed to aid rangers in their work to prevent wildfire hazards. One of the most successful sysems was developed by the German aerospace center DLR (Deutsches Zentrum für Luft- und Raumfahrt) and relies on sophisticated hand-crafted feature. The algorithm behind this system is called fshell.

Convolutional neural networks (CNN) are specialized artificial neural networks that are the state-of-the-art for image recognition tasks. It is therefore investigated if these trainable models can be applied to the wildfire dectection problem to improve the performance of existing systems. Besides CNNs that use spatial features only, C3D networks that can also extract temporal features are considered. To tackle the detection of smoke in a larger image, a selective search variant was developed, that preselects regions of observable motion, which are then classified by the actual models.

The results clearly show that the trained networks learned to distinguish wildfire smoke from other objects, although they do not reach the fshell's performance. However, fshell makes use of additional prior knowledge whereas the CNNs rely on image data only. The results also show that C3D networks are the best performing single models, suggesting that the use of temporal features is important for accurate detection.

Betreuer
Prof. Dr. R. Rojas, Tim Landgraf
Abschluss
Master of Science (M.Sc.)
Abgabedatum
20.09.2015

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  • Masterarbeit Hohberg
be-digital Pressekonferenz am 07.12.15Mexico Oktober 2015MiG Mexico 2015Finalisten German Open 2014Simulator-Erfinder: Professor Raul Rojas (l.) und David Dormagen von der AG Intelligente Systeme und RobotikMadeInGermany in MexicoThe Tony Sale Award winners 2014: Robert B Garner (L) and  Raul Rojas (R), Nov. 2014Able und BakerCarolo-Cup-Team2014Formalisierung und Automatisierung von Gödels GottesbeweisAutoNOMOS-Team 2011Besuch Senatorin Yzer am 22.03.13Die autonomen Fahrzeuge der AG Intelligente Systeme und RobotikArchaeocopterMulticopterEntwicklung einer Roboterbiene

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