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Pradeep Kumar Ladi
Observed name:
PRADEEP KUMAR LADI
Institution:
GIET University
Observed institution:
GIET University
ORCID:
0000-0003-2277-0252
Observed ORCID:
0000-0003-2277-0252
OpenAlex ID:
A5072721776
A Novel Grey Wolf Optimisation based CNN Classifier for Hyperspectral Image classification
2022
·
Sandeep Kumar Ladi
, G. K. Panda
, et al.
·
Multimedia Tools and Applications
·
24
PKNNet: a novel feature learning architecture for vegetation mapping using remote sensing hyperspectral image classification
2023
·
Pradeep Kumar Ladi
, Murali Gopal Kakita
, et al.
·
Earth Science Informatics
·
8
A novel strategy for classifying spectral-spatial shallow and deep hyperspectral image features using 1D-EWT and 3D-CNN
2022
·
Sandeep Kumar Ladi
, G K Panda
, et al.
·
Earth Science Informatics
·
7
PDF
Hyperspectral Image Classification Using SWT and CNN
2019
·
Sandeep Kumar Ladi
, Ratnakar Dash
, et al.
·
7
A Pioneering Approach of Hyperspectral Image Classification Employing the Cooperative Efforts of 3D, 2D and Depthwise Separable-1D Convolutions
2022
·
Sandeep Kumar Ladi
, G. K. Panda
, et al.
·
IEEE International Symposium on Sustainable Energy, Signal Processing and Cyber Security (iSSSC)
·
4
Correction to: A novel grey wolf optimisation based CNN classifier for hyperspectral image classification
2022
·
Sandeep Kumar Ladi
, G. K. Panda
, et al.
·
Multimedia Tools and Applications
·
4
PDF
SWTNet: hyperspectral image classification using two-stage combined shallow and deep feature extraction
2022
·
Pradeep Kumar Ladi
, Murali Gopal Kakita
, et al.
·
Neural Computing and Applications
·
2
HybridSSCN: Analysis Of Hierarchical Feature Learning Architecture Using Blended Conv3D And DepthwiseConv2D For Hyperspectral Image Classification
2022
·
Pradeep Kumar Ladi
, Murali Gopal Kakita
, et al.
·
OITS International Conference on Information Technology (OCIT)
·
1
HybridMSSN: A Deep Learning Hyperspectral Image Classification Model
2022
·
SANDEEP KUMAR LADI
, G K PANDA
, et al.
·
Research Square
PDF
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Works count:
9
Citation count:
57
H-index:
4
I10-index:
1
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