Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers?

26 August 2019

Papers citing "Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers?"

7 / 7 papers shown

Title
Managing the unknown: a survey on Open Set Recognition and tangential areas Marcos Barcina-Blanco J. Lobo Pablo Garcia-Bringas Javier Del Ser VLM 39 2 0 14 Dec 2023
Analysis and Applications of Deep Learning with Finite Samples in Full Life-Cycle Intelligence of Nuclear Power Generation Chenwei Tang Wenqiang Zhou Dong Wang Caiyang Yu Zhenan He ... Shudong Huang Yi Gao Jianming Chen Wentao Feng Jiancheng Lv AI4CE 36 0 0 07 Nov 2023
OpenTAL: Towards Open Set Temporal Action Localization Wentao Bao Qi Yu Yu Kong EDL 37 26 0 10 Mar 2022
A Survey of Uncertainty in Deep Neural Networks J. Gawlikowski Cedrique Rovile Njieutcheu Tassi Mohsin Ali Jongseo Lee Matthias Humt ... R. Roscher Muhammad Shahzad Wen Yang R. Bamler Xiaoxiang Zhu BDL UQCV OOD 63 1,112 0 07 Jul 2021
Deep Open Intent Classification with Adaptive Decision Boundary Hanlei Zhang Hua Xu Ting-En Lin VLM 23 103 0 18 Dec 2020
A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning Martin Mundt Yongjun Hong Iuliia Pliushch Visvanathan Ramesh CLL 30 146 0 03 Sep 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,167 0 06 Jun 2015