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Quality-Aware Modular Deep Learning Approach for Weed Segmentation
Brian Gopalan
,
Nathalia Nascimento
,
Vishal Monga
Electrical Engineering
Research output
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Dive into the research topics of 'Quality-Aware Modular Deep Learning Approach for Weed Segmentation'. Together they form a unique fingerprint.
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Keyphrases
Quality-aware
100%
Deep Learning
100%
Modular Deep Learning
100%
Weed Segmentation
100%
Noise Reduction
33%
Agriculture
33%
Decoder
33%
Computational Efficiency
33%
Mean Absolute Deviation
33%
Laplacian
33%
Routing Strategy
33%
Quality Efficiency
33%
Quality Condition
33%
Precision Agriculture
33%
Image Degradation
33%
Segmentation Quality
33%
Transformer Model
33%
Richardson-Lucy
33%
Drone Images
33%
Drone Video
33%
CNN-based Methods
33%
Degradation Type
33%
Modified Transformer
33%
Preprocessing Model
33%
Fisher Vector Encoding
33%
Vision Transformer Model
33%
Computer Science
Learning Approach
100%
Deep Learning Method
100%
Drone
66%
Transformer Model
66%
Computational Efficiency
33%
Preprocessing
33%
Learning Framework
33%
Routing Strategy
33%
Processing Model
33%
Laplace Operator
33%
Convolutional Neural Network
33%
Vision Transformer
33%
Engineering
Learning Approach
100%
Deep Learning Method
100%
Drone
66%
Computational Efficiency
33%
Absolute Deviation
33%
Laplace Operator
33%
Convolutional Neural Network
33%
Segmentation Quality
33%
Earth and Planetary Sciences
Noise Reduction
100%
Preprocessing
100%
Precision Agriculture
100%
Computational Efficiency
100%