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
94 2018 Normalized Spectral Similarity Score ( RR Nidamanuri, B Zbell
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2010
75 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
64 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
51 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
49 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
48 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
43 2013 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
40 2021 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
39 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
35 2019 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
33 2014 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
32 2016 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
31 2015 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
31 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
30 2019 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
22 2019 Spectral identification of materials by reflectance spectral library search RR Nidamanuri, AM Ramiya
Geocarto International 29 (6), 609-624, 2014
21 2014 Hyperspectral discrimination of tea plant varieties using machine learning, and spectral matching methods RR Nidamanuri
Remote Sensing Applications: Society and Environment 19, 100350, 2020
20 2020 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
20 2020 Semantic labelling of urban point cloud data AM Ramiya, RR Nidamanuri, R Krishnan
The International Archives of the Photogrammetry, Remote Sensing and Spatial …, 2014
20 2014 