ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1909.01498
  4. Cited By
Demystifying Brain Tumour Segmentation Networks: Interpretability and
  Uncertainty Analysis

Demystifying Brain Tumour Segmentation Networks: Interpretability and Uncertainty Analysis

3 September 2019
Parth Natekar
Avinash Kori
Ganapathy Krishnamurthi
ArXivPDFHTML

Papers citing "Demystifying Brain Tumour Segmentation Networks: Interpretability and Uncertainty Analysis"

2 / 2 papers shown
Title
Influence based explainability of brain tumors segmentation in
  multimodal Magnetic Resonance Imaging
Influence based explainability of brain tumors segmentation in multimodal Magnetic Resonance Imaging
Tommaso Torda
Andrea Ciardiello
Simona Gargiulo
Greta Grillo
Simone Scardapane
Cecilia Voena
S. Giagu
21
0
0
05 Apr 2024
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
276
9,136
0
06 Jun 2015
1