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RAI-Net: Tomato Plant Disease Classification Using Residual-Attention-Inception Network
Ritesh Maurya
, Lucky Rajput
,
Satyajit Mahapatra
*
*
Corresponding author for this work
School of Computer Engineering
Research output
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INIS
classification
100%
tomatoes
100%
plant diseases
100%
diseases
50%
detection
50%
extraction
33%
yields
33%
crops
33%
interventions
16%
pathogens
16%
prediction
16%
losses
16%
accuracy
16%
learning
16%
images
16%
output
16%
mapping
16%
economic impact
16%
dollars
16%
Biochemistry, Genetics and Molecular Biology
Disease Classification
100%
Feature Extraction
100%
Infectious Agent
50%
Earth and Planetary Sciences
Pattern Recognition
100%
Crop Yield
100%
Mapping Method
50%
Agricultural and Biological Sciences
Plant Diseases
100%
Deep Learning Method
50%
Engineering
Mapping Method
50%