Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2012.03061
Cited By
A Survey on Deep Learning with Noisy Labels: How to train your model when you cannot trust on the annotations?
SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), 2020
5 December 2020
F. Cordeiro
G. Carneiro
NoLa
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"A Survey on Deep Learning with Noisy Labels: How to train your model when you cannot trust on the annotations?"
24 / 24 papers shown
A deep multiple instance learning approach based on coarse labels for high-resolution land-cover mapping
Remote Sensing (RS), 2023
Gianmarco Perantoni
Lorenzo Bruzzone
183
0
0
08 Oct 2025
Ordinal Adaptive Correction: A Data-Centric Approach to Ordinal Image Classification with Noisy Labels
Alireza Sedighi Moghaddam
Mohammad Reza Mohammadi
245
0
0
02 Sep 2025
Balancing Accuracy, Calibration, and Efficiency in Active Learning with Vision Transformers Under Label Noise
Moseli Motsóehli
Hope Mogale
Kyungim Baek
322
0
0
07 May 2025
ATM-Net: Anatomy-Aware Text-Guided Multi-Modal Fusion for Fine-Grained Lumbar Spine Segmentation
Sheng Lian
Dengfeng Pan
Jianlong Cai
Guang-Yong Chen
Zhun Zhong
Shaozi Li
Shen Zhao
Shuo Li
309
4
0
04 Apr 2025
Improving Label Error Detection and Elimination with Uncertainty Quantification
Johannes Jakubik
Michael Vossing
M. Maskey
Christopher Wolfle
G. Satzger
151
2
0
15 May 2024
Exploring the Robustness of In-Context Learning with Noisy Labels
Chen Cheng
Xinzhi Yu
Haodong Wen
Jinsong Sun
Guanzhang Yue
Yihao Zhang
Zeming Wei
NoLa
384
15
0
28 Apr 2024
Noisy Label Processing for Classification: A Survey
Mengting Li
Chuang Zhu
NoLa
386
10
0
05 Apr 2024
Semi-Supervised Dialogue Abstractive Summarization via High-Quality Pseudolabel Selection
Jianfeng He
Hang Su
Jason (Jinglun) Cai
Igor Shalyminov
Hwanjun Song
Saab Mansour
236
8
0
06 Mar 2024
Differences Between Hard and Noisy-labeled Samples: An Empirical Study
SDM (SDM), 2023
Mahsa Forouzesh
Patrick Thiran
NoLa
253
4
0
20 Jul 2023
Mesogeos: A multi-purpose dataset for data-driven wildfire modeling in the Mediterranean
Neural Information Processing Systems (NeurIPS), 2023
Spyros Kondylatos
Ioannis Prapas
Gustau Camps-Valls
Ioannis Papoutsis
238
24
0
08 Jun 2023
A Survey on the Robustness of Computer Vision Models against Common Corruptions
Shunxin Wang
Raymond N. J. Veldhuis
Christoph Brune
N. Strisciuglio
OOD
VLM
683
26
0
10 May 2023
Deep Active Learning in the Presence of Label Noise: A Survey
Moseli Motsóehli
Kyungim Baek
NoLa
VLM
327
5
0
22 Feb 2023
Active Learning Framework to Automate NetworkTraffic Classification
Jaroslav Pesek
Dominik Soukup
T. Čejka
215
1
0
26 Oct 2022
A Survey of Dataset Refinement for Problems in Computer Vision Datasets
ACM Computing Surveys (ACM CSUR), 2022
Zhijing Wan
Zhixiang Wang
CheukTing Chung
Zheng Wang
390
17
0
21 Oct 2022
A Study on the Impact of Data Augmentation for Training Convolutional Neural Networks in the Presence of Noisy Labels
SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), 2022
E. Santana
G. Carneiro
F. Cordeiro
NoLa
335
9
0
23 Aug 2022
Unsupervised Frequent Pattern Mining for CEP
G. Shapira
Assaf Schuster
87
1
0
28 Jul 2022
Compressing Features for Learning with Noisy Labels
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Yingyi Chen
S. Hu
Xin Shen
C. Ai
Johan A. K. Suykens
NoLa
195
23
0
27 Jun 2022
How to Find Actionable Static Analysis Warnings: A Case Study with FindBugs
IEEE Transactions on Software Engineering (TSE), 2022
Rahul Yedida
Hong Jin Kang
Huy Tu
Xueqi Yang
David Lo
Tim Menzies
212
19
0
21 May 2022
Optical Remote Sensing Image Understanding with Weak Supervision: Concepts, Methods, and Perspectives
IEEE Geoscience and Remote Sensing Magazine (GRSM), 2022
Jun Yue
Leyuan Fang
Pedram Ghamisi
Weiying Xie
Jun Li
Jocelyn Chanussot
Antonio J. Plaza
203
57
0
18 Apr 2022
Transfer and Marginalize: Explaining Away Label Noise with Privileged Information
International Conference on Machine Learning (ICML), 2022
Mark Collier
Rodolphe Jenatton
Efi Kokiopoulou
Jesse Berent
284
19
0
18 Feb 2022
AI Total: Analyzing Security ML Models with Imperfect Data in Production
Awalin Sopan
Konstantin Berlin
161
3
0
13 Oct 2021
Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks
Curtis G. Northcutt
Anish Athalye
Jonas W. Mueller
500
654
0
26 Mar 2021
TrustNet: Learning from Trusted Data Against (A)symmetric Label Noise
Amirmasoud Ghiassi
Taraneh Younesian
Robert Birke
L. Chen
NoLa
167
6
0
13 Jul 2020
Combating noisy labels by agreement: A joint training method with co-regularization
Computer Vision and Pattern Recognition (CVPR), 2020
Jianguo Huang
Lei Feng
Xiangyu Chen
Bo An
NoLa
1.0K
656
0
05 Mar 2020
1
Page 1 of 1
