Active and Continuous Exploration with Deep Neural Networks and Expected Model Output Changes

19 December 2016

Papers citing "Active and Continuous Exploration with Deep Neural Networks and Expected Model Output Changes"

9 / 9 papers shown

Title
Uncertainty Herding: One Active Learning Method for All Label Budgets Wonho Bae Gabriel L. Oliveira Danica J. Sutherland UQCV 241 0 0 30 Dec 2024
Two-Step Active Learning for Instance Segmentation with Uncertainty and Diversity Sampling Ke Yu Yuanmin Tang Giulia DeSalvo Suraj Kothawade Abdullah Rashwan S. Tavakkol Kayhan Batmanghelich Xiaoqi Yin ISeg 32 0 0 28 Sep 2023
Making Look-Ahead Active Learning Strategies Feasible with Neural Tangent Kernels Mohamad Amin Mohamadi Wonho Bae Danica J. Sutherland 32 20 0 25 Jun 2022
Domain Adaptation and Active Learning for Fine-Grained Recognition in the Field of Biodiversity Bernd Gruner Matthias Körschens Björn Barz Joachim Denzler 22 0 0 22 Oct 2021
Semi-Supervised Active Learning with Temporal Output Discrepancy Siyu Huang Tianyang Wang Haoyi Xiong Jun Huan Dejing Dou UQCV 30 66 0 29 Jul 2021
Multiple instance active learning for object detection Tianning Yuan Fang Wan Mengying Fu Jianzhuang Liu Songcen Xu Xiangyang Ji QiXiang Ye WSOD 41 121 0 06 Apr 2021
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
Multi-modal Active Learning From Human Data: A Deep Reinforcement Learning Approach Ognjen Rudovic Meiru Zhang Bjorn Schuller Rosalind W. Picard OffRL 36 44 0 07 Jun 2019
Learning Loss for Active Learning Donggeun Yoo In So Kweon UQCV 36 652 0 09 May 2019