Optimized Neural Architecture for Automatic Landslide Detection from High‐Resolution Airborne Laser Scanning Data

article by Mustafa Ridha Mezaal et al published 16 July 2017 in Applied sciences

Optimized Neural Architecture for Automatic Landslide Detection from High‐Resolution Airborne Laser Scanning Data is …
instance of (P31):
scholarly articleQ13442814

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P356DOI10.3390/APP7070730

P50authorBiswajeet PradhanQ57414806
P2093author name stringHelmi Zulhaidi Mohd Shafri
Maher Ibrahim Sameen
Mustafa Ridha Mezaal
Zainuddin Md Yusoff
P2860cites workLong short-term memoryQ24805158
Comparing supervised and unsupervised multiresolution segmentation approaches for extracting buildings from very high resolution imageryQ42150728
Wrappers for feature subset selectionQ56689295
Data Fusion Technique Using Wavelet Transform and Taguchi Methods for Automatic Landslide Detection From Airborne Laser Scanning Data and QuickBird Satellite ImageryQ57598161
Regional landslide susceptibility analysis using back-propagation neural network model at Cameron Highland, MalaysiaQ57598415
Landslide inventory maps: New tools for an old problemQ59003441
P275copyright licenseCreative Commons Attribution 4.0 InternationalQ20007257
P6216copyright statuscopyrightedQ50423863
P433issue7
P921main subjectautomationQ184199
landslideQ167903
P304page(s)730
P577publication date2017-07-16
P1433published inApplied SciencesQ27725631
P1476titleOptimized Neural Architecture for Automatic Landslide Detection from High‐Resolution Airborne Laser Scanning Data
P478volume7

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cites work (P2860)
Q57598045Automatic landslide detection using Dempster–Shafer theory from LiDAR-derived data and orthophotos
Q57598041Oil Palm Counting and Age Estimation from WorldView-3 Imagery and LiDAR Data Using an Integrated OBIA Height Model and Regression Analysis

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