A Survey of Deep Active Learning

Cited by (1,006)

Items 601–700 of 1,006

1. An active ensemble classifier for detecting animal sequences from global camera trap data
   Tommi Mononen, Bess Hardwick, Sandra Alcobia, Adrian Barrett, Gergin Blagoev, Stéphane Boyer, Paula Gonçalves, Brigitte Gottsberger, Elli Groner, Chris Ho et al. · 2025 · Methods in Ecology and Evolution
2. Temporal Model-Based Federated Active Medical Image Classification
   Yunlu Yan, Chun-Mei Feng, Yuexiang Li, Jinheng Xie, Jun Chen, Mohamed Elhoseiny, Ming Hu, Kaishun Wu, Lei Zhu · 2025 · Lecture notes in computer science
3. HERE: Hierarchical Active Exploration of Radiance Field With Epistemic Uncertainty Minimization
   Taekbeom Lee, Dabin Kim, Youngseok Jang, H. Jin Kim · 2026 · IEEE Robotics and Automation Letters
4. MSMM: Multiple Strategy Fusion Enhanced Global Mobility Prediction Model for Off-Road Autonomous Vehicles
   Chen Hua, Jie Chen, Biao Yu, Jinde Cao, Imre J. Rudas · 2026 · IEEE Transactions on Vehicular Technology
5. Supervoxel-based and Cost-Effective Active Learning for Point Cloud Semantic Segmentation
   Shanding Ye, Yongjian Fu, Hu Lin, Zhe Yin, Zhijie Pan · 2022 · IEEE International Conference on Intelligent Transportation Systems (ITSC)
6. Efficient labeling of retinal fundus photographs using deep active learning
   S. K. Paul, I. Pan, W. Sobol · 2022 · Journal of Medical Imaging
7. The Impacts of Quality-Oriented Dataset Labeling on Tree Cover Segmentation Using U-Net: A Case Study in WorldView-3 Imagery
   Tao Jiang, Maximilian Freudenberg, Christoph Kleinn, Alexander S. Ecker, Nils Nölke · 2023 · Remote Sensing
8. An active federated method driven by inter-client informativeness variability of labeled data
   Funa Zhou, Chang Wang, Xiong Hu, Chaoge Wang, Tianzhen Wang · 2023 · Signal Image and Video Processing
9. Good Time to Ask: A Learning Framework for Asking for Help in Embodied Visual Navigation
   Jenny Zhang, Samson S. Yu, Jiafei Duan, Cheston Tan · 2023 · International Conference on Ubiquitous Robots (UR)
10. Automated defect detection on inductive thermography images using supervised and semi-supervised Deep Learning methods
    Karim Tout, Naïm Samet, Patrick Bouteille · 2023 · e-Journal of Nondestructive Testing
11. An innovative deep active learning approach for improving unlabeled audio classification by selectively querying informative instance
    Mohamed SalahEldin Salama · 2023 · International Journal of Engineering Business Management
12. A Human-Centered AI Framework for Efficient Labelling of ECGs From Drug Safety Trials
    Mously Dior Diaw, Stéphane Papelier, Alexandre Durand-Salmon, Jacques Felblinger, Julien Oster · 2023 · IEEE Transactions on Biomedical Engineering
13. Active Learning in Feature Extraction for Glass-in-Glass Detection
    Jerzy Rapcewicz, Marcin Malesa · 2024 · Electronics
14. Semi-supervised active learning using convolutional auto- encoder and contrastive learning
    Hezi Roda, A. Geva · 2024 · Frontiers Artif. Intell.
15. Inversion of biophysical parameters of potato based on an active learning pool-based sampling strategy
    Yuanyuan Ma, Xiaoyu Song, Jie Zhang, Di Lin Pan, Haikuan Feng, Guijun Yang, Chunxia Qiu, Heguang Sun, Chunkai Zheng, Pingping Li · 2024 · International Journal of Remote Sensing
16. On the Topology Awareness and Generalization Performance of Graph Neural Networks
    Junwei Su, Chuan Wu · 2024 · Lecture notes in computer science
17. ARS-Flow 2.0: An enhanced design space exploration flow for accelerator-rich system based on active learning
    S. L. Huang, Yuyang Ye, Hao Yan, Longxing Shi · 2024 · Integration
18. Discovering ensembles of small language models out of scarcely labelled data for fake news detection
    Gianluigi Folino, Massimo Guarascio, Luigi Pontieri, Paolo Zicari · 2025 · Applied Soft Computing
19. Tıbbi Görüntülemede Derin Üretken Modeller : Bir Literatür Taraması
    Begüm Şener · 2025 · Journal of Polytechnic
20. Combining X-Vectors and Bayesian Batch Active Learning: Two-Stage Active Learning Pipeline for Speech Recognition
    Ognjen Kundačina, Vladimir Vincan, Dragiša Mišković · 2025 · IEEE Transactions on Audio Speech and Language Processing
21. On resource consumption of machine learning in communications network security
    Md Muzammal Hoque, Ijaz Ahmad, Jani Suomalainen, Paolo Dini, Mohammad Tahir · 2025 · Computer Networks
22. Uncertainty Aware Training to Improve Uncertainty Active Learning for Semantic Segmentation
    Moritz Thoma, Tobias Preintner, Emad Aghajanzadeh, Shambhavi Balamuthu Sampath, Pierpaolo Mori, Nael Fasfous, Manoj Rohit Vemparala, Alexander Frickenstein, Daniel Mueller-Gritschneder, Ulf Schlichtmann · 2025 · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
23. Dynamic Confidence Variance for Generalized Coreset in Active Learning
    Tian-Jiao Wan, Zi-Jian Gao, Xudong Gong, Da-Wei Feng, Xing-Xing Zhang, Bo Ding, Yi-Jie Wang, Huai-Min Wang, Ke-Le Xu · 2026 · IEEE transactions on circuits and systems for video technology (Print)
24. Novel models to predict stored melon fruit marketability using convolutional neural networks
    Michael Alabboud, Siamak Kalantari, Forouzandeh Soltani · 2022 · Journal of Ambient Intelligence and Humanized Computing
25. Enabling Weakly Supervised Temporal Action Localization From On-Device Learning of the Video Stream
    Yue Tang, Yawen Wu, Peipei Zhou, Jingtong Hu · 2022 · IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
26. Reducing Annotation Effort by Identifying and Labeling Contextually Diverse Classes for Semantic Segmentation Under Domain Shift
    Sharat Agarwal, Saket Anand, Chetan Arora · 2023 · IEEE Winter Conference on Applications of Computer Vision
27. High-information data-centric weed images data identification system based on triple filter for smart agriculture
    Shukun Ma, Zhuo Zhang · 2023 · Journal of Electronic Imaging
28. Reinforced active learning for CVD-grown two-dimensional materials characterization
    Zebin Li, Fei Yao, Hongyue Sun · 2023 · IISE Transactions
29. Health Crowd Sensing and Computing: From Crowdsourced Digital Health Footprints to Population Health Intelligence
    Jiangtao Wang, Long Fei Chen, Xu Wang · 2023 · Wireless networks
30. ENLD: Efficient Noisy Label Detection for Incremental Datasets in Data Lake
    Xuanke You, Lan Zhang, Junyang Wang, Zhimin Bao, Yunfei Wu, Shuaishuai Dong · 2023 · IEEE International Conference on Data Engineering (ICDE)
31. Improving Classroom Dialogue Act Recognition from Limited Labeled Data with Self-Supervised Contrastive Learning Classifiers
    Vikram Kumaran, Jonathan Rowe, Bradford Mott, Snigdha Chaturvedi, James C. Lester · 2023 · Findings of the Association for Computational Linguistics: ACL (Findings of ACL)
32. Towards Professional Level Crowd Annotation of Expert Domain Data
    Pei Wang, Nuno M. Vasconcelos · 2023 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
33. Bayesian Posterior Approximation With Stochastic Ensembles
    Oleksandr Balabanov, B. Mehlig, Hampus Linander · 2023 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
34. AdaDS: Adaptive data selection for accelerating pre-trained language model knowledge distillation
    Qinhong Zhou, Peng Li, Yang Liu, Yuyang Guan, Qizhou Xing, Ming Chen, Maosong Sun, Yang Liu · 2023 · AI Open
35. PLVI-CE: a multi-label active learning algorithm with simultaneously considering uncertainty and diversity
    Yan Gu, Jicong Duan, Hualong Yu, Xibei Yang, Shang Gao · 2023 · Applied Intelligence
36. Active Learning Based Domain Adaptation for Tissue Segmentation of Histopathological Images
    Saul Fuster, Farbod Khoraminia, Trygve Christian Eftestøl, Tahlita C.M. Zuiverloon, Kjersti Engan · 2023 · European Signal Processing Conference (EUSIPCO)
37. Data Augmentation Based on Active Virtual Sample Selection for Bearing Fault Diagnosis
    Zeyu Song, Xiaoyu Jiang, Wei Yu, Jinchuan Qian, Zhihuan Song · 2023 · CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)
38. Semantic Trajectory Planning for Industrial Robotics
    Zhou Li, Gengming Xie, Varsha Arya, Kwok Tai Chui · 2023 · International Journal on Semantic Web and Information Systems
39. Memory-augmented Variational Adaptation for Online Few-shot Segmentation
    Jie Liu, Yingjun Du, Zehao Xiao, Cees G. M. Snoek, Jan‐Jakob Sonke, Efstratios Gavves · 2023 · IEEE International Conference on Computer Vision Workshops
40. An Integrated Active Deep Learning Approach for Image Classification from Unlabeled Data with Minimal Supervision
    Amira Abdelwahab, Ahmed Afifi, Mohamed SalahEldin Salama · 2023 · Electronics
41. Open-World Continual Learning: A Framework
    Sahisnu Mazumder, Bing Liu · 2024 · Synthesis lectures on human language technologies
42. Rethinking deep active learning for medical image segmentation: A diffusion and angle-based framework
    Linhao Qu, Qiuye Jin, Kexue Fu, Manning Wang, Zhijian Song · 2024 · Biomedical Signal Processing and Control
43. Combination of generic novelty detection and supervised classification pipelines for industrial condition monitoring
    Steffen Klein, Yannick Wilhelm, Andreas Schütze, Tizian Schneider · 2024 · tm - Technisches Messen
44. Generalized Synchronized Active Learning for Multi-Agent-Based Data Selection on Mobile Robotic Systems
    Sebastian Schmidt, Lukas Stappen, Leo Schwinn, Stephan Günnemann · 2024 · IEEE Robotics and Automation Letters
45. Applied Federated Model Personalization in the Industrial Domain: A Comparative Study
    Ilias Siniosoglou, Vasileios Argyriou, George F. Fragulis, Panagiotis Fouliras, Georgios Th. Papadopoulos, Anastasios Lytos, Panagiotis G. Sarigiannidis · 2024 · IEEE Open Journal of the Communications Society
46. SBC-AL: Structure and Boundary Consistency-Based Active Learning for Medical Image Segmentation
    Taimin Zhou, Jin Yang, Lingguo Cui, Nan Zhang, Senchun Chai · 2024 · Lecture notes in computer science
47. AnesFormer: An End-to-End Framework for EEG-Based Anesthetic State Classification
    Qihang Wang, Ying Hao Chen, Qinge Xiao · 2024 · IEEE Transactions on Big Data
48. Active Learning for Forward/Inverse Kinematics of Redundantly-driven Flexible Tensegrity Manipulator
    Yuhei Yoshimitsu, Takayuki Osa, Heni Ben Amor, Shuhei Ikemoto · 2024 · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
49. Deep Active Learning with Range Feedback for Facial Age Estimation
    Aditya Bhattacharya, Shayok Chakraborty · 2022 · International Joint Conference on Neural Networks (IJCNN)
50. Marich: A Query-efficient Distributionally Equivalent Model Extraction Attack using Public Data
    Pratik Karmakar, Debabrota Basu · 2023 · HAL
51. Active Learning for Video Classification with Frame Level Queries
    Debanjan Goswami, Shayok Chakraborty · 2023 · International Joint Conference on Neural Networks (IJCNN)
52. Active Learning for Multiple Target Models
    Sheng-Jun Huang, Yi Li, Ying-Peng Tang · 2025 · IEEE Transactions on Pattern Analysis and Machine Intelligence
53. Graph-Based Active Machine Learning Method for Diverse and Novel Antimicrobial Peptides Generation and Selection
    Bonaventure F. P. Dossou, Dianbo Liu, Ji Xu, Moksh J. Jain, Almer M. van der Sloot, Roger Palou, Michael D. Tyers, Yoshua Bengio · 2022 · Research Square
54. Exploring the frontiers of chemistry with a generalreactive machine learning potential
    Shuhao Zhang, Małgorzata Z. Makoś, Ryan B. Jadrich, Elfi Kraka, Kipton M. Barros, Benjamin T. Nebgen, Sergei Tretiak, Olexandr Isayev, Nicholas Lubbers, Richard A. Messerly et al. · 2022 · ChemRxiv
55. JaxSGMC: Modular stochastic gradient MCMC in JAX
    Stephan Thaler, Paul Fuchs, Ana Cukarska, Julija Zavadlav · 2024 · SoftwareX
56. Introduction to Medical Image Segmentation: Overview of Modalities, Benchmark Datasets, Data Augmentation Techniques, and Evaluation Metrics
    Aasia Rehman, Suhail Qadir Mir · 2025
57. Technical Report on the Pangram AI-Generated Text Classifier
    Emi, Bradley, Spero, Max · 2024 · arXiv
58. Adaptive Generation of Training Data for ML Reduced Model Creation
    Mark R. Cianciosa, Richard K. Archibald, Wael R Elwasif, Ana Gainaru, Jin Myung Park, R. E. Whitfield · 2022 · IEEE International Conference on Big Data (BigData)
59. iSSL-AL: a deep active learning framework based on self-supervised learning for image classification
    Rand Agha, Ahmad M. Mustafa, Qusai Abuein · 2024 · Neural Computing and Applications
60. Approximating Memorization Using Loss Surface Geometry for Dataset Pruning and Summarization
    Andrea Agiollo, Young In Kim, Rajiv Khanna · 2024 · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
61. Class-Balancing Deep Active Learning with Auto-Feature Mixing and Minority Push-Pull Sampling
    Hongxin Lin, Chu Zhang, Mingyu Wang, Bin Huang, Jingjing Shao, Jinxiang Zhang, Zhenhua Gao, Xianfen Diao, Bingsheng Huang · 2024 · Lecture notes in computer science
62. An Active Transfer Learning framework for image classification based on Maximum Differentiation Classifier
    Peng Zan, Yuerong Wang, Haohao Hu, Wanjun Zhong, Tianyu Han, Jingwei Yue · 2024 · Image and Vision Computing
63. Online multi-fidelity data aggregation via hierarchical neural network
    Chunlong Hai, Jiazhen Wang, Shimin Guo, Weiqi Qian, Liquan Mei · 2025 · Computer Methods in Applied Mechanics and Engineering
64. Efficiency is the rule: Domain adaptive semantic segmentation with minimal annotations
    Tianyu Huai, Junhang Zhang, Xingjiao Wu, Jian Jin, Liang He · 2025 · Expert Systems with Applications
65. Complementary Learning System Theory-based Active Learning for Audio Classification
    Hui Geng, Zijian Gao, Tianjiao Wan, Dawei Feng, Changjian Wang, Kele Xu · 2025 · IEEE International Conference on Acoustics Speech and Signal Processing
66. Batch active learning for time-series classification with multi-mode exploration
    Sangho Lee, Chihyeon Choi, Hyungrok Do, Youngdoo Son · 2025 · Information Sciences
67. Deep Active Learning for Image Hierarchical Classification by Introducing Dependencies and Constraints Between Classes
    Yan-Xue Wu, Min Wang, Fan Min, Qi Wang, Zhiheng Zhang, Haoyu Zhang, Xiangbing Zhou · 2025 · IEEE Transactions on Systems, Man & Cybernetics. Systems
68. The Insight-Inference Loop: Efficient Text Classification via Natural Language Inference and Threshold-Tuning
    Sandrine Chausson, Marion Fourcade, David James Harding, Björn Roß, Grégory Renard · 2025 · Sociological Methods & Research
69. Quantifying Uncertainty in Deep Learning: Methods, Challenges, and Future Directions
    Simegnew Yihunie Alaba, Yuichi Motai · 2026 · IEEE Transactions on Emerging Topics in Computational Intelligence
70. Cyber Social Threats: A Data-centric AI Perspective
    Adita Kulkarni · 2025 · ACM Southeast Regional Conference (ACMSE)
71. Land use and land cover classification on high-resolution UAV images for heavy rainfall hazard maps using deep neural networks
    Dennis Sprute, Hanne Hendrickx, Pedro Zamboni, Muhtasimul Islam Rushdi, Florian Brodrecht, Anette Eltner, Holger Flatt · 2025 · Remote Sensing Applications Society and Environment
72. Cross-platform laser powder bed fusion process-property modeling with active transfer learning
    Qiaojie Zheng, Michael B. Wakin, Joy Gockel, Craig Brice, Xiaoli Zhang · 2025 · Journal of Manufacturing Processes
73. A Unified Conceptual Hybrid Framework for the Automated Assessment of Short Answers
    Vidasha Ramnarain-Seetohul, Yasmine Z. Rosunally, Vandana Bassoo · 2025 · International Journal of Artificial Intelligence in Education
74. A Multi-Strategy Active Learning Framework for Enhanced Peripheral Blood Cell Image Detection
    Yuheng Feng, Jiangtao He, Linjin Wang, Wuchen Yang, Sihan Deng, Lanlin Li, Xinwei Li · 2025 · IEEE Access
75. Sel4FT: Annotation Selection for Pretraining-Finetuning With Distribution Shift
    Han Lu, Yichen Xie, Mingyu Ding, Wei Zhan, Xiaokang Yang, Masayoshi Tomizuka, Junchi Yan · 2025 · IEEE Transactions on Pattern Analysis and Machine Intelligence
76. LGMM: Local-to-global multi-scale accelerated mobility map prediction for unmanned ground vehicles
    Chen Hua, Chunmao Jiang, Yuliang Wei, Ziyu Chen, Xinkai Kuang, Jianhua Yin · 2026 · Neurocomputing
77. Active metric learning with hybrid information for ordinal classification
    Mengzi Tang, Bernard De Baets C · 2025 · Neurocomputing
78. Inconsistency-Based Active Learning for LiDAR Object Detection
    Esteban Rivera, Loïc Stratil, Markus Lienkamp · 2025 · IEEE Intelligent Vehicles Symposium
79. Autonomous machine learning
    Wenwu Zhu, Xin Wang, Zongben Xu · 2025 · Scientia Sinica Informationis
80. Efficient dataset construction using active learning and uncertainty-aware neural networks for plasma turbulent transport surrogate models
    A. Ho, Lorenzo Zanisi, B. de Leeuw, V. Galvan, Pablo Rodriguez-Fernandez, Nathan T. Howard · 2025 · Physics of Plasmas
81. Active Learning for Transformer-Based Fault Diagnosis in 5G and Beyond Mobile Networks
    Seyed Soheil Johari, Massimo Tornatore, Nashid Shahriar, Raouf Boutaba, Aladdin Saleh · 2025 · IEEE Transactions on Network and Service Management
82. Extracting Embeddings for Active Learning Corresponding to Regions of Interest in an Image
    V. A. Sokolov, Ivan A. Matveev, Lev Teplyakov · 2025 · Pattern Recognition and Image Analysis
83. Fully differentiable sensor placement and informative path planning
    Kalvik Jakkala, Srinivas Akella · 2025 · The International Journal of Robotics Research
84. Designing Synthetic Active Learning for model refinement in manufacturing parts detection
    Xiaomeng Zhu, Jacob Henningsson, Pär Mårtensson, Lars Hanson, Mårten Björkman, Atsuto Maki · 2025 · Journal of Manufacturing Systems
85. Advances in intelligent defect recognition method for oil and gas pipeline weld X-ray image
    Wei-Chao Qian, Shao-Hua Dong, Meng Sun, Zi-Cong Han, Lin Chen · 2025 · Petroleum Science
86. A Novel Multiscale Residual Active Deep Q -Learning Network for Intelligent Bearing Fault Diagnosis With Small Training Data
    Chao Chen, Wenhui Sun, Hui Wang, Haobo Yang, L. Han, Wei Fan · 2025 · IEEE Transactions on Instrumentation and Measurement
87. DALEK: combining deep active learning and explanations methods for fake news detection on COVID-19
    Carmela Comito, Massimo Guarascio, Angelica Liguori, Francesco Sergio Pisani · 2026 · Neural Computing and Applications
88. Active learning for optimal feature combination selection in machine learning of TBM operational data
    Chen-Hao Zhang, Yu Wang, Xu Li · 2026 · Automation in Construction
89. SAREM: Semi-supervised Active Heterogeneous Entity Matching Framework
    Jinxiu Du, Tiezheng Nie, Wenzhou Dou, Derong Shen, Yue Kou · 2022 · Lecture notes in computer science
90. VERIPS: Verified Pseudo-label Selection for Deep Active Learning
    Sandra Gilhuber, Philipp Jahn, Yunpu Ma, Thomas Seidl · 2022 · Proceedings
91. DLP: towards active defense against backdoor attacks with decoupled learning process
    Zonghao Ying, Bin Lin Wu · 2023 · Cybersecurity
92. Exploiting Deep Learning and Explanation Methods for Movie Tag Prediction
    Erica Coppolillo, Massimo Guarascio, Marco Minici, Francesco Sergio Pisani · 2023 · International Database Engineering and Applications Symposium (IDEAS)
93. Deep Active Learning for Left Ventricle Segmentation in Echocardiography
    Eman Alajrami, Preshen Naidoo, Jevgeni Jevsikov, Elisabeth S. Lane, Jamie Pordoy, Nasim Dadashi Serej, Neda Azarmehr, Fateme Dinmohammadi, Matthew James Shun-Shin, Dárrel P. Francis et al. · 2023 · Lecture notes in computer science
94. Uncertainty Aware Active Learning for Reconfiguration of Pre-trained Deep Object-Detection Networks for New Target Domains
    Jiaming Na, Varuna De-Silva · 2023 · 2023 IEEE IAS Global Conference on Emerging Technologies (GlobConET)
95. On the use of Query by Committee for Human-in-the-Loop Named Entity Recognition
    Gabriel Corvino, Vitor Vasconcelos De Oliveira, Angelo C. Mendes da Silva, Ricardo Marcondes Marcacini · 2022 · Anais do Symposium on Knowledge Discovery, Mining and Learning (KDMiLe)
96. OODA loop for learning open-world novelty problems
    Pamul Yadav, Shiho Kim · 2023 · Advances in computers
97. Confidence-Based Federated Distillation for Vision-Based Lane-Centering
    Yitao Chen, Dawei Chen, Haoxin Wang, Kyungtae Han, Ming Zhao · 2023 · IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)
98. Analysis on the Legal System of International Technology Trade Management Based on Data Mining Analysis
    Xiangbin Zuo, Yi Yang · 2023 · International Journal on Semantic Web and Information Systems
99. TACTFUL: A Framework for Targeted Active Learning for Document Analysis
    Venkatapathy Subramanian, Sagar Poudel, Parag Chaudhuri, Ganesh Ramakrishnan · 2023 · Lecture notes in computer science
100. How to Overcome Confirmation Bias in Semi-Supervised Image Classification by Active Learning
     Sandra Gilhuber, Rasmus Hvingelby, Mang Ling Ada Fok, Thomas Seidl · 2023 · Lecture notes in computer science