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Image Search Results


Benchmarking table-showing comparison of proposed and existing segmentation models.

Journal: Diagnostics

Article Title: Segmentation-Based Classification Deep Learning Model Embedded with Explainable AI for COVID-19 Detection in Chest X-ray Scans

doi: 10.3390/diagnostics12092132

Figure Lengend Snippet: Benchmarking table-showing comparison of proposed and existing segmentation models.

Article Snippet: Alom et al. 2020) [ ] , NABLA-N network Accuracy—94.66 Dice—88.46 Jaccard—86.50 , Kaggle (390 + 234) , Inception Recurrent Residual Neural Network (IRRCNN) model , 3 class-87.26% , 10.19% , 0.93.

Techniques: Comparison

Benchmarking table-showing comparison of proposed and existing classification (solo) models.

Journal: Diagnostics

Article Title: Segmentation-Based Classification Deep Learning Model Embedded with Explainable AI for COVID-19 Detection in Chest X-ray Scans

doi: 10.3390/diagnostics12092132

Figure Lengend Snippet: Benchmarking table-showing comparison of proposed and existing classification (solo) models.

Article Snippet: Alom et al. 2020) [ ] , NABLA-N network Accuracy—94.66 Dice—88.46 Jaccard—86.50 , Kaggle (390 + 234) , Inception Recurrent Residual Neural Network (IRRCNN) model , 3 class-87.26% , 10.19% , 0.93.

Techniques: Comparison

Benchmarking table showing a comparison of proposed and existing segmentation-based classification models.

Journal: Diagnostics

Article Title: Segmentation-Based Classification Deep Learning Model Embedded with Explainable AI for COVID-19 Detection in Chest X-ray Scans

doi: 10.3390/diagnostics12092132

Figure Lengend Snippet: Benchmarking table showing a comparison of proposed and existing segmentation-based classification models.

Article Snippet: Alom et al. 2020) [ ] , NABLA-N network Accuracy—94.66 Dice—88.46 Jaccard—86.50 , Kaggle (390 + 234) , Inception Recurrent Residual Neural Network (IRRCNN) model , 3 class-87.26% , 10.19% , 0.93.

Techniques: Comparison