A Survey of Deep Active Learning

Ren, Pengzhen, Xiao, Yun, Chang, Xiaojun, Huang, Po-Yao, Li, Zhihui, Gupta, Brij B., Chen, Xiaojiang, Wang, Xin·2022·ACM Computing Surveys
DOI 10.1145/3472291

Cited by (1,006)

Items 301–400 of 1,006

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  2. Photovoltaic Cell Defect Detection Based on Weakly Supervised Learning With Module-Level Annotations
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  3. Combining Synthetic Images and Deep Active Learning: Data-Efficient Training of an Industrial Object Detection Model
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  4. An interpretable deep learning model to map land subsidence hazard
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  6. Fail or pass? Investigating learning experiences and interactive roles in MOOC discussion board
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  7. ORALI: Open-set recognition and active learning for unknown lithology identification
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  8. Toward Long Form Audio-Visual Video Understanding
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  9. Federated Active Learning with Transfer Learning: Empowering Edge Intelligence for Enhanced Lung Cancer Diagnosis
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  10. Human-in-the-loop: Using classifier decision boundary maps to improve pseudo labels
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  11. A deep reinforcement active learning method for multi-label image classification
    Qing Cai, Ran Tao, Xiufen Fang, Xiurui Xie, Guisong Liu · 2025 · Computer Vision and Image Understanding
  12. Federated continual learning for vision-based plastic classification in recycling
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  13. Active Learning for Human-in-the-Loop Customs Inspection
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  14. KaIDA: a modular tool for assisting image annotation in deep learning
    Marcel P. Schilling, Svenja Schmelzer, Lukas Klinger, Markus Reischl · 2022 · Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics
  15. Informative Path Planning for Active Learning in Aerial Semantic Mapping
    Julius Ruckin, Liren Jin, Federico Magistri, C. Stachniss, Marija Popović · 2022 · IEEE/RJS International Conference on Intelligent RObots and Systems
  16. Randomness is the Root of All Evil: More Reliable Evaluation of Deep Active Learning
    Yilin Ji, Daniel Kaestner, O. Wirth, Christian Wressnegger · 2023 · IEEE Workshop/Winter Conference on Applications of Computer Vision
  17. Tensor-Empowered Adaptive Learning for Few-Shot Streaming Tasks
    Bocheng Ren, Laurence Tianruo Yang, Qingchen Zhang, Jun Feng, Xin Nie · 2023 · IEEE Transactions on Neural Networks and Learning Systems
  18. Research on classification method of high myopic maculopathy based on retinal fundus images and optimized ALFA-Mix active learning algorithm
    Shaojun Zhu, Maonian Wu, Bo Zheng, Bang-Quan Liu, Shao-Chong Zhang, Weihua Yang · 2023 · International Journal of Ophthalmology
  19. Counterfactual Active Learning for Out-of-Distribution Generalization
    Xun Deng, Wenjie Wang, Fuli Feng, Hanwang Zhang, Xiangnan He, Yong Liao · 2023 · Proceedings of the conference - Association for Computational Linguistics. Meeting
  20. Modularity in Deep Learning: A Survey
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  21. Exploring the frontiers of chemistry with a generalreactive machine learning potential
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  22. A review and systematic guide to counteracting medical data scarcity for AI applications
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  23. Synergizing advanced materials and artificial intelligence for next-generation carbon capture, utilization, and storage (CCUS): a review
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  24. Temporal Output Discrepancy for Loss Estimation-Based Active Learning
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  25. An active learning convolutional neural network for predicting river flow in a human impacted system
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  26. Active Learning-Based Sample Selection for Label-Efficient Blind Image Quality Assessment
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  27. Bayesian Estimate of Mean Proper Scores for Diversity-Enhanced Active Learning
    Wei Tan, Lan Du, W. Buntine · 2023 · IEEE Transactions on Pattern Analysis and Machine Intelligence
  28. Agile Modeling: From Concept to Classifier in Minutes
    Otilia Stretcu, Edward B. Vendrow, Kenji Hata, Krishnamurthy Viswanathan, Vittorio Ferrari, Sasan Tavakkol, Wenlei Zhou, Aditya Avinash, Enming Luo, Neil Alldrin et al. · 2023 · IEEE/CVF International Conference on Computer Vision (ICCV)
  29. Using machine learning to link electronic health records in cancer registries: On the tradeoff between linkage quality and manual effort
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  30. Effective drug-target affinity prediction via generative active learning
    Yuansheng Liu, Zhenran Zhou, Xiaofeng Cao, Dongsheng Cao, Xiangxiang Zeng · 2024 · Information Sciences
  31. Linked Color Imaging with Artificial Intelligence Improves the Detection of Early Gastric Cancer
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  32. Deep active learning with high structural discriminability for molecular mutagenicity prediction
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  33. Less Is More: Unlocking Semi-Supervised Deep Learning for Vulnerability Detection
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  34. Weakly Supervised Deep Learning for Arabic Tweet Sentiment Analysis on Education Reforms: Leveraging Pre-Trained Models and LLMs With Snorkel
    Alanoud Fahad Alotaibi, Farrukh Nadeem, Mohamed Hamdy · 2025 · IEEE Access
  35. A data-efficient active learning architecture for anomaly detection in industrial time series data
    David Holtz, Can Kaymakci, Daniel Leuthe, Simon Wenninger, Alexander Sauer · 2025 · Flexible Services and Manufacturing Journal
  36. A review of weed image identification based on deep few-shot learning
    Enhui Wu, Yu Chen, Ruijun Ma, Xiande Zhao · 2025 · Computers and Electronics in Agriculture
  37. Uncertainty-guided Bayesian active learning for cost-effective fault diagnosis with minimal labeled data
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  38. The Lean Data Scientist
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  39. A deep learning workflow for weak reflection extraction in pitch-catch measurements in the cased hole
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    Kyeongtak Han, Youngeun Kim, Dongyoon Han, Hojun Lee, Sungeun Hong · 2023 · Neural Networks
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    Zhengliang Xiang, Xuhui He, Yunfeng Zou, Haiquan Jing · 2023 · Structural Health Monitoring
  42. Human–Machine Interactive Learning Method Based on Active Learning for Smart Workshop Dynamic Scheduling
    Dongyuan Wang, Liuen Guan, Juan Liu, Chen Ding, Fei Qiao · 2023 · IEEE Transactions on Human-Machine Systems
  43. Active Learning for Stacking and AdaBoost-Related Models
    Qun Sui, Sujit Kumar Ghosh · 2024 · Stats
  44. Image fusion using online convolutional sparse coding
    Chengfang Zhang, Ziyou Zhang, Ziliang Feng · 2022 · Journal of Ambient Intelligence and Humanized Computing
  45. Deep Structural Estimation: With an Application to Option Pricing
    Hui Chen, Antoine Didisheim, Simon Scheidegger · 2021 · SSRN Electronic Journal
  46. Scene Graphs: A Survey of Generations and Applications.
    Xiaojun Chang, Pengzhen Ren, Pengfei Xu, Zhihui Li, Xiaojiang Chen, Alex G. Hauptmann · 2021 · arXiv (Cornell University)
  47. SurFF: a foundation model for surface exposure and morphology across intermetallic crystals
    Jun Yin, Honghao Chen, Ju Qiu, Wentao Li, Peng He, Jiali Li, Iftekhar A. Karimi, Xiaocheng Lan, Tiefeng Wang, Xiaonan Wang · 2025 · Nature Computational Science
  48. Deep Feature Learning From Electromyographic Signals for Gesture Recognition Systems
    Wenjuan Zhong, Xinyu Jiang, Katarzyna Szymaniak, Milad Jabbari, Chenfei Ma, Kianoush Nazarpour · 2025 · IEEE Transactions on Neural Systems and Rehabilitation Engineering
  49. Morphologic Features and Deep Learning–Based Analysis of Canine Spermatogenic Stages
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    Anureet Chhabra, Sarjana Singh, Akash Sharma, Sudhakar Kumar, Brij Bhooshan Gupta, Varsha Arya, Kwok Tai Chui · 2024 · International Conference on Consumer Electronics
  52. Human in the loop active learning for time-series electrical measurement data
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  54. Active Learning for Vision-Language Models
    Bardia Safaei, Vishal M. Patel · 2025 · IEEE Winter Conference on Applications of Computer Vision
  55. Clustering investigation of scramjet combustion processes based on contrastive learning
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  57. High-efficient low-cost characterization of composite material properties using domain-knowledge-guided self-supervised learning
    Binglin Xie, Xianhua Yao, Weining Mao, Mohammad Hossein Rafiei, Nan Hu · 2022 · Computational Materials Science
  58. Machine Learning-Based Label Quality Assurance for Object Detection Projects in Requirements Engineering
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  59. Deep Active Alignment of Knowledge Graph Entities and Schemata
    Jiacheng Huang, Zequn Sun, Qijin Chen, Xiaozhou Xu, Weijun Ren, Wei Ping Hu · 2023 · Proceedings of the ACM on Management of Data
  60. Federated Active Semi-Supervised Learning With Communication Efficiency
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  61. Neural-physics multi-fidelity model with active learning and uncertainty quantification for GPU-enabled microfluidic concentration gradient generator design
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  63. Optimal Subsampling via Predictive Inference
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  64. Active learning of data-assimilation closures using graph neural networks
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  65. TrustAL: Trustworthy Active Learning Using Knowledge Distillation
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  66. An ensemble active learning for a fluidized bed granulation in the pharmaceutical industry
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  67. Active Learning for Deep Visual Tracking
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  68. Topic-Guided Sampling For Data-Efficient Multi-Domain Stance Detection
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  69. EdgeTran: Device-Aware Co-Search of Transformers for Efficient Inference on Mobile Edge Platforms
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  70. AMAD: Active learning-based multivariate time series anomaly detection for large-scale IT systems
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  71. ARS-Flow: A Design Space Exploration Flow for Accelerator-rich System based on Active Learning
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  72. Near-infrared spectral expansion method based on active semi-supervised regression
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  73. Towards Exploring the Limitations of Test Selection Techniques on Graph Neural Networks: An Empirical Study
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  74. Contrastive Open-Set Active Learning-Based Sample Selection for Image Classification
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  75. Uncertainty pattern and an integration strategy in flood susceptibility modeling: Limited sample size
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  76. Enabling Real-Time Inference in Online Continual Learning via Device-Cloud Collaboration
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  77. Defending industrial internet of things against Modbus/TCP threats: A combined AI-based detection and SDN-based mitigation solution
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  79. Generalized Active Stratified Sampling for Non-IID Data
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  83. Density-based one-shot active learning for image segmentation
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  88. Deep Unsupervised Active Learning on Learnable Graphs
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