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Effective Evaluation of Deep Active Learning on Image Classification
  Tasks

Effective Evaluation of Deep Active Learning on Image Classification Tasks

16 June 2021
Nathan Beck
D. Sivasubramanian
Apurva Dani
Ganesh Ramakrishnan
Rishabh K. Iyer
    VLM
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Papers citing "Effective Evaluation of Deep Active Learning on Image Classification Tasks"

9 / 9 papers shown
Title
Towards Comparable Active Learning
Towards Comparable Active Learning
Thorben Werner
Johannes Burchert
Lars Schmidt-Thieme
81
0
0
24 Feb 2025
LabelBench: A Comprehensive Framework for Benchmarking Adaptive
  Label-Efficient Learning
LabelBench: A Comprehensive Framework for Benchmarking Adaptive Label-Efficient Learning
Jifan Zhang
Yifang Chen
Gregory H. Canal
Stephen Mussmann
Arnav M. Das
...
Yinglun Zhu
Jeffrey Bilmes
S. Du
Kevin G. Jamieson
Robert D. Nowak
VLM
33
10
0
16 Jun 2023
STREAMLINE: Streaming Active Learning for Realistic Multi-Distributional
  Settings
STREAMLINE: Streaming Active Learning for Realistic Multi-Distributional Settings
Nathan Beck
Suraj Kothawade
Pradeep Shenoy
Rishabh K. Iyer
16
2
0
18 May 2023
Evaluating the effect of data augmentation and BALD heuristics on
  distillation of Semantic-KITTI dataset
Evaluating the effect of data augmentation and BALD heuristics on distillation of Semantic-KITTI dataset
Ngoc Phuong Anh Duong
Alexandre Almin
Léo Lemarié
B. R. Kiran
27
0
0
21 Feb 2023
Navya3DSeg -- Navya 3D Semantic Segmentation Dataset & split generation
  for autonomous vehicles
Navya3DSeg -- Navya 3D Semantic Segmentation Dataset & split generation for autonomous vehicles
Alexandre Almin
Léo Lemarié
Ngoc Phuong Anh Duong
B. R. Kiran
3DPC
31
9
0
16 Feb 2023
Algorithm Selection for Deep Active Learning with Imbalanced Datasets
Algorithm Selection for Deep Active Learning with Imbalanced Datasets
Jifan Zhang
Shuai Shao
Saurabh Verma
Robert D. Nowak
26
20
0
14 Feb 2023
An Empirical Study on the Efficacy of Deep Active Learning for Image
  Classification
An Empirical Study on the Efficacy of Deep Active Learning for Image Classification
Yu Li
Mu-Hwa Chen
Yannan Liu
Daojing He
Qiang Xu
34
9
0
30 Nov 2022
Understanding and Preventing Capacity Loss in Reinforcement Learning
Understanding and Preventing Capacity Loss in Reinforcement Learning
Clare Lyle
Mark Rowland
Will Dabney
CLL
36
109
0
20 Apr 2022
LiDAR dataset distillation within bayesian active learning framework:
  Understanding the effect of data augmentation
LiDAR dataset distillation within bayesian active learning framework: Understanding the effect of data augmentation
Ngoc Phuong Anh Duong
Alexandre Almin
Léo Lemarié
B. R. Kiran
18
3
0
06 Feb 2022
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