基于卷积神经网络的野外烟雾检测研究.docx

基于卷积神经网络的野外烟雾检测研究为题目，写不少于1200的论文
摘要：
野外火灾是一种常见的自然灾害，这也造成了巨大的经济损失和生命安全问题。因此，及早发现和掌握野外火灾燃烧状态至关重要。在本研究中，我们提出了一种基于卷积神经网络的野外烟雾检测方法。通过在收集的烟雾图像数据集上进行实验，我们证明了该方法的高准确性和鲁棒性和高效性。烟雾检测的可靠性和准确性对于及早预警和扑灭野外火灾至关重要。
关键词：野外火灾，烟雾检测，卷积神经网络
Introduction
Wildfireisacommonnaturaldisaster,whichcausessignificanteconomiclossesandthreatstohumanlife.Therefore,earlydetectionandmonitoringofwildfireisofcrucialimportance.Smokeisoneoftheprimarysignsofawildfire,anditsearlydetectioncanhelpfiredepartmentsrespondmorequicklytopreventspreadandquicklyextinguishthefire.Thus,thedevelopmentofasurveillancesystemthatcandetectandrecognizesmokeisimportant.Inrecentyears,computervisiontechniqueshaveshowngreatpotentialinsolvingvariousreal-worldproblems,includingsmokedetection.Convolutionalneuralnetworks(CNNs)areatypeofdeeplearningalgorithmthathasbeenshowntobeeffectiveinimagerecognitionandclassificationtasks.
Inthisstudy,weproposeanapproachtodetectsmokeinthewildusingaCNN.Theproposedmethodconsistsofthreemainsteps:imagepreprocessing,featureextraction,andclassification.Theperformanceoftheproposedapproachisevaluatedusingadatasetthatcontainssmokeimagescollectedfromvarioussources,includingsatelliteimages,CCTVcameras,andunmannedaerialvehicles.Ourexperimentsshowthattheproposedapproachachieveshighaccuracyandrobustnessinsmokedetection.
Methodology
Theproposedapproachconsistsofthreemainsteps:
ImagePreprocessing
Imagepreprocessingisanimportantstepinanyimageanalysistask.Intheproposedapproach,weuseimagepreprocessingtoremoveimagenoiseandenhancethecontrastofthesmokeimages.First,weapplyaGaussianfiltertotheimagetoremovenoise.Then,weusecontraststretchingtoenhancethecontrastofthesmokeregion.
FeatureExtraction
Featureextractionistheprocessofextractingmeaningfulfeaturesfromtheimagethatarerelevanttothetaskathand.Inourstudy,weuseapre-trainedCNNmodelasafeatureextractor.WeusetheconvolutionallayersoftheCNNmodeltoextractfeaturesfromthepreprocessedsmokeimages.Thesefeaturesarethenpassedthroughafullyconnectedlayertoobtainafeaturevectorthatrepresen