Specificity (SP), sensitivity (SN), F1-Score, Matthews correlation coefficient (MCC), and accuracy (ACC) for classification of nuclei types. by Anjir Ahmed Chowdhury (21696531)

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An Overview of the proposed framework. by Anjir Ahmed Chowdhury (21696531)

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Performance analysis of different FL algorithms on both models. by Anjir Ahmed Chowdhury (21696531)

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Average mPQ and bPQ of the nuclei labels across the 19 different tissue types in the PanNuke dataset. by Anjir Ahmed Chowdhury (21696531)

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Performance comparison of federated learning algorithms for nucleus segmentation with INT8 quantized models. by Anjir Ahmed Chowdhury (21696531)

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CPA and IoU comparison of different segmentation models. by Anjir Ahmed Chowdhury (21696531)

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Average PQ of each nucleus category. by Anjir Ahmed Chowdhury (21696531)

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Performance of the different combinations for the SegNet and the DenseNet121 models. by Anjir Ahmed Chowdhury (21696531)

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Search space for segmentation and classification models. by Anjir Ahmed Chowdhury (21696531)

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Performance analysis of different quantization techniques on latency, energy consumption, and size. by Anjir Ahmed Chowdhury (21696531)

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An overview of the PanNuke nuclei distribution across the nineteen tissue types, sorted by the total number of nuclei within each tissue. by Anjir Ahmed Chowdhury (21696531)

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Quantitative evaluation of different segmentation models. by Anjir Ahmed Chowdhury (21696531)

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Class-wise performance of the classification models for categorizing nucleus. by Anjir Ahmed Chowdhury (21696531)

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Pre-process PanNuke dataset [15] for nuclei instance segmentation and classification. by Anjir Ahmed Chowdhury (21696531)

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Compare the performance of the proposed framework with other state-of-the-art frameworks. by Anjir Ahmed Chowdhury (21696531)

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