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Subject Syllabus

AD-803 (A) - AI for Remote Sensing

AIDS · Semester 8

Course Modules

Learn topic-wise with Hyper AI and revise using mapped PYQs.

Definition of Remote sensingPrinciples of Remote SensingIntroduction to Artificial IntelligenceIntegration of AI in Remote Sensing
Sensors: Types and classification of sensorsPlatforms: Types of platforms, ground, airborne, and space born platforms Remote Sensing Data Acquisition and Pre-processing Data acquisition techniques and image resolutionData pre-processing and feature extraction techniquesRadiometric and geometric correctionsData fusion and enhancement methods
Supervised Learning for Remote Sensing AnalysisUnsupervised Learning for Remote Sensing AnalysisDeep Learning for Remote Sensing AnalysisImage Image Classification Techniques in Remote Sensing.
Object detection and tracking in remote sensing imageryChange detection and time-series analysisHyperspectral and LiDAR data analysisFusion of multi-modal remote sensing data.
Land cover and land use mappingEnvironmental monitoring and assessmentDisaster management and responsePrecision agriculture and crop monitoring.R-mi Cresson, "Deep Learning for Remote Sensing Images with Open Source Software", CRC Press, 1st edition,2020. 2.Moulay A AkhloufiMozhdehShahbazi,"Deep Learning Methods for Remote Sensing",MDPI AG, 2022. 3.Alka RaniNirmal KumarSinghSinhaJenaHimeshPatra, "Remote Sensing Data Analysis Using R",CRC PressTaylor & Francis Group,2021. 4.Tammy E.PareceJohn A.McGeeJames B.Campbell, "Remote Sensing with ArcGIS Pro",2019.