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Cost-Effective Training of Deep CNNs with Active Model Adaptation

Cost-Effective Training of Deep CNNs with Active Model Adaptation

15 February 2018
Sheng-Jun Huang
Jia-Wei Zhao
Zhao-Yang Liu
ArXivPDFHTML

Papers citing "Cost-Effective Training of Deep CNNs with Active Model Adaptation"

10 / 10 papers shown
Title
Divide and Adapt: Active Domain Adaptation via Customized Learning
Divide and Adapt: Active Domain Adaptation via Customized Learning
Duojun Huang
Jichang Li
Weikai Chen
Jun Steed Huang
Z. Chai
Guanbin Li
42
25
0
21 Jul 2023
Dirichlet-based Uncertainty Calibration for Active Domain Adaptation
Dirichlet-based Uncertainty Calibration for Active Domain Adaptation
Mixue Xie
Shuang Li
Rui Zhang
Chi Harold Liu
UQCV
41
29
0
27 Feb 2023
MADAv2: Advanced Multi-Anchor Based Active Domain Adaptation
  Segmentation
MADAv2: Advanced Multi-Anchor Based Active Domain Adaptation Segmentation
Munan Ning
Donghuan Lu
Yujia Xie
Dongdong Chen
Dong Wei
Yefeng Zheng
Yonghong Tian
Shuicheng Yan
Liuliang Yuan
35
9
0
18 Jan 2023
Deep Active Learning with Budget Annotation
Deep Active Learning with Budget Annotation
P. Gikunda
23
0
0
31 Jul 2022
Learning Distinctive Margin toward Active Domain Adaptation
Learning Distinctive Margin toward Active Domain Adaptation
Ming-Kun Xie
Yuxi Li
Yabiao Wang
Zekun Luo
Zhenye Gan
Zhongyi Sun
M. Chi
Chengjie Wang
Pei Wang
36
31
0
11 Mar 2022
Active Learning for Open-set Annotation
Active Learning for Open-set Annotation
Kun-Peng Ning
Xun Zhao
Yu Li
Sheng-Jun Huang
22
35
0
18 Jan 2022
Convex Online Video Frame Subset Selection using Multiple Criteria for
  Data Efficient Autonomous Driving
Convex Online Video Frame Subset Selection using Multiple Criteria for Data Efficient Autonomous Driving
Soumik Das
Harikrishna Patibandla
S. Bhattacharya
Kshounis Bera
Niloy Ganguly
Sourangshu Bhattacharya
33
0
0
24 Mar 2021
Weakly Supervised Vessel Segmentation in X-ray Angiograms by Self-Paced
  Learning from Noisy Labels with Suggestive Annotation
Weakly Supervised Vessel Segmentation in X-ray Angiograms by Self-Paced Learning from Noisy Labels with Suggestive Annotation
Jingyang Zhang
Guotai Wang
Hongzhi Xie
Shuyang Zhang
Ning Huang
Shaoting Zhang
Lixu Gu
35
41
0
27 May 2020
Are All Training Examples Created Equal? An Empirical Study
Are All Training Examples Created Equal? An Empirical Study
Kailas Vodrahalli
Ke Li
Jitendra Malik
23
59
0
30 Nov 2018
Bayesian Convolutional Neural Networks with Bernoulli Approximate
  Variational Inference
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference
Y. Gal
Zoubin Ghahramani
UQCV
BDL
213
745
0
06 Jun 2015
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