Rama Rao Nidamanuri
Cited by
Cited by
Estimation of vegetable crop parameter by multi-temporal UAV-borne images
T Moeckel, S Dayananda, RR Nidamanuri, S Nautiyal, N Hanumaiah, ...
Remote Sensing 10 (5), 805, 2018
Normalized Spectral Similarity Score () as an Efficient Spectral Library Searching Method for Hyperspectral Image Classification
RR Nidamanuri, B Zbell
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2010
Segmentation based building detection approach from LiDAR point cloud
AM Ramiya, RR Nidamanuri, R Krishnan
The Egyptian Journal of Remote Sensing and Space Science 20 (1), 71-77, 2017
Use of field reflectance data for crop mapping using airborne hyperspectral image
RR Nidamanuri, B Zbell
ISPRS Journal of photogrammetry and remote sensing 66 (5), 683-691, 2011
Dynamic linear classifier system for hyperspectral image classification for land cover mapping
BB Damodaran, RR Nidamanuri
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2014
Dynamic ensemble selection approach for hyperspectral image classification with joint spectral and spatial information
BB Damodaran, RR Nidamanuri, Y Tarabalka
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2015
Spectral material mapping using hyperspectral imagery: a review of spectral matching and library search methods
S Vishnu, RR Nidamanuri, R Bremananth
Geocarto international 28 (2), 171-190, 2013
A supervoxel-based spectro-spatial approach for 3D urban point cloud labelling
AM Ramiya, RR Nidamanuri, K Ramakrishnan
International Journal of Remote Sensing 37 (17), 4172-4200, 2016
Multi-scale dilated residual convolutional neural network for hyperspectral image classification
K Pooja, RR Nidamanuri, D Mishra
2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution …, 2019
Object-oriented semantic labelling of spectral–spatial LiDAR point cloud for urban land cover classification and buildings detection
AM Ramiya, RR Nidamanuri, R Krishnan
Geocarto international 31 (2), 121-139, 2016
Assessment of the impact of dimensionality reduction methods on information classes and classifiers for hyperspectral image classification by multiple classifier system
BB Damodaran, RR Nidamanuri
Advances in Space Research 53 (12), 1720-1734, 2014
Transferring spectral libraries of canopy reflectance for crop classification using hyperspectral remote sensing data
RR Nidamanuri, B Zbell
Biosystems engineering 110 (3), 231-246, 2011
Terrestrial laser scanner based 3D reconstruction of trees and retrieval of leaf area index in a forest environment
I Indirabai, MVH Nair, RN Jaishanker, RR Nidamanuri
Ecological informatics 53, 100986, 2019
Seasonal variations in phenology and productivity of a tropical dry deciduous forest from MODIS and Hyperion
B Christian, N Joshi, M Saini, N Mehta, S Goroshi, RR Nidamanuri, ...
Agricultural and Forest Meteorology 214, 91-105, 2015
Object-level classification of vegetable crops in 3D LiDAR point cloud using deep learning convolutional neural networks
R Jayakumari, RR Nidamanuri, AM Ramiya
Precision Agriculture 22 (5), 1617-1633, 2021
Individual tree detection from airborne laser scanning data based on supervoxels and local convexity
AM Ramiya, RR Nidamanuri, R Krishnan
Remote Sensing Applications: Society and Environment 15, 100242, 2019
A method for selecting optimal spectral resolution and comparison metric for material mapping by spectral library search
RR Nidamanuri, B Zbell
Progress in Physical Geography 34 (1), 47-58, 2010
Spectral identification of materials by reflectance spectral library search
RR Nidamanuri, AM Ramiya
Geocarto International 29 (6), 609-624, 2014
3-D imaging techniques and review of products
DS Pankaj, RR Nidamanuri, PB Prasad
Proceedings of International Conference on" Innovations in Computer Science …, 2013
Direct estimation of leaf area index of tropical forests using LiDAR point cloud
I Indirabai, MVH Nair, JR Nair, RR Nidamanuri
Remote Sensing Applications: Society and Environment 18, 100295, 2020
The system can't perform the operation now. Try again later.
Articles 1–20