ResearchTrend.AI
Enhancing Deep Learning Model Explainability in Brain Tumor Datasets using Post-Heuristic Approaches

Enhancing Deep Learning Model Explainability in Brain Tumor Datasets using Post-Heuristic Approaches

Konstantinos Pasvantis
Eftychios E. Protopapadakis
    AAML
ArXivPDFHTML

Papers citing "Enhancing Deep Learning Model Explainability in Brain Tumor Datasets using Post-Heuristic Approaches"

6 / 6 papers shown
Title
A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAI
A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAI
Erico Tjoa
Cuntai Guan
XAI
73
1,427
0
17 Jul 2019
Going Deep in Medical Image Analysis: Concepts, Methods, Challenges and Future Directions
Going Deep in Medical Image Analysis: Concepts, Methods, Challenges and Future Directions
F. Altaf
Syed Mohammed Shamsul Islam
Naveed Akhtar
N. Janjua
OOD
45
200
0
15 Feb 2019
Learning Transferable Architectures for Scalable Image Recognition
Learning Transferable Architectures for Scalable Image Recognition
Barret Zoph
Vijay Vasudevan
Jonathon Shlens
Quoc V. Le
129
5,577
0
21 Jul 2017
Identity Mappings in Deep Residual Networks
Identity Mappings in Deep Residual Networks
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
257
10,149
0
16 Mar 2016
Rethinking the Inception Architecture for Computer Vision
Rethinking the Inception Architecture for Computer Vision
Christian Szegedy
Vincent Vanhoucke
Sergey Ioffe
Jonathon Shlens
Z. Wojna
3DV
BDL
390
27,231
0
02 Dec 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
711
99,991
0
04 Sep 2014

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.