摘要
Alargenumberofdebrisflowdisasters(calledSeismicdebrisflows)wouldoccurafteranearthquake,whichcancauseagreatamountofdamage.UAVlow-altituderemotesensingtechnologyhasbecomeameansofquicklyobtainingdisasterinformationasithastheadvantageofconvenienceandtimeliness,butthespectralinformationoftheimageissoscarce,makingitdifficulttoaccuratelydetecttheinformationofearthquakedebrisflowdisasters.Basedontheaboveproblems,aseismicdebrisflowdetectionmethodbasedontransferlearning(TL)mechanismisproposed.Onthebasisoftheconstructedseismicdebrisflowdisasterdatabase,thefeaturesacquiredfromthetrainingoftheconvolutionalneuralnetwork(CNN)aretransferredtothedisasterinformationdetectionoftheseismicdebrisflow.Theautomaticdetectionofearthquakedebrisflowdisasterinformationisthencompleted,andtheresultsofobject-orientedseismicdebrisflowdisasterinformationdetectionarecomparedandanalyzedwiththedetectionresultssupportedbytransferlearning.
出版日期
2019年01月11日（中国期刊网平台首次上网日期，不代表论文的发表时间）
