Deep-CNN-and-geometric-features-based-gastrointestinal-tract
Deep-CNN-and-geometric-features-based-gastrointestinal-tract-diseases-detection-and-classification-f
Deep CNN and geometric features-based gastrointestinal tract diseases detection and classification from wireless capsule endoscopy images Muhammad Sharif, Muhammad Attique Khan, Muhammad Rashid, Mussarat Yasmin, Farhat Afza, Urcun John Tanik (Journal of Experimental & Theoretical Artificial Intelligence: IF 2.11 | 02-02-2019)
Figure 1: Sample collected WCE images
Proposed Model
Contrast Elongating
Lesion Detection
Figure 5: Proposed probability based color features clustering effects
Figure 6: Results after morphological operations
Deep CNN Features Extraction
Figure 7: Utilized architecture of VGG16 for deep CNN features extraction
Figure 8: Employed architecture of VGG19 for features extraction
Figure 9: Proposed features fusion and selection approach
Results and Discussion
Citation pour cette source
Muhammad Rashid (2024). Deep-CNN-and-geometric-features-based-gastrointestinal-tract (https://github.com/rashidrao-pk/Deep-CNN-and-geometric-features-based-gastrointestinal-tract-diseases-detection-and-classification-f), GitHub. Récupéré le .
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Version | Publié le | Notes de version | |
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1.0.0 |
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