Fisher-based inaccuracy measure in terms of survival function: Applications in reliability and image segmentation

Key Points

• The fisher-based accuracy measure improves reliability estimates, enhancing applications in image segmentation techniques.
• This study evaluates survival functions to assess prediction accuracy, revealing significant potential in various contexts.
• Assessment using the fisher-based methodology highlights its utility in improving both image segmentation accuracy and reliability metrics.
• Findings suggest that adopting this inaccuracy measure could lead to increased reliability in predictive models and applications.