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optimising the segmentation process in Deep Convolutional Neural Networks by solving the anomaly due to fine edges

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CYBORG-NIT-ROURKELA/Improving_Semantic_segmentation

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Class_selection

Class_selection

 
 

Images

Images

 
 

Interconversion

Interconversion

 
 

Flowchart_doc.docx

Flowchart_doc.docx

 
 

README.md

README.md

 
 

alt_main.py

alt_main.py

 
 

collage_generator.py

collage_generator.py

 
 

kde.py

kde.py

 
 

main.py

main.py

 
 

meanshift main.py

meanshift main.py

 
 

meanshift_using_kde.ipynb

meanshift_using_kde.ipynb

 
 

miou_calculation.py

miou_calculation.py

 
 

results.txt

results.txt

 
 

select.py

select.py

 
 

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Improving Semantic Segmentation Through Clustering

This repository is the implmenatation of the article, Disparting, wich propose a noble method for optimisng the segmentation process in Deep Convolutional Neural Networks by solving the anomaly due to fine edges. Our overall pipeline

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optimising the segmentation process in Deep Convolutional Neural Networks by solving the anomaly due to fine edges

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clustering pytorch transfer-learning semantic-segmentation deeplab-resnet watershed watershed-algorithm meanshift deeplabv3 deeplab-v3-plus pytorch-implementation disparting

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