Super-trustscore: reliable failure detection for automated skin lesion diagnosis
The successful deployment of deep neural networks in safetycritical settings, such as medical image analysis, is contingent on their ability to provide reliable uncertainty estimates. In this paper, we propose a new confidence scoring function called Super-TrustScore that improves upon the existing...
Main Authors: | Naushad, J, Voiculescu, ID |
---|---|
Format: | Conference item |
Sprog: | English |
Udgivet: |
IEEE
2024
|
Lignende værker
-
Automated Skin Lesion Detection towards Melanoma
af: Maryam Bibi, et al.
Udgivet: (2019-10-01) -
AI EMPOWERED DIAGNOSIS OF PEMPHIGUS: A MACHINE LEARNING APPROACH FOR AUTOMATED SKIN LESION DETECTION
af: Mamun Ahmed, et al.
Udgivet: (2023-12-01) -
Exploring Edge-Based Segmentation Towards Automated Skin Lesion Diagnosis
af: Lau, Hui Keng, et al.
Udgivet: (2018) -
Conditional Random Fields and Supervised Learning in Automated Skin Lesion Diagnosis
af: Paul Wighton, et al.
Udgivet: (2011-01-01) -
Automated stroke lesion detection and diagnosis system
af: Mohd Saad, N., et al.
Udgivet: (2017)