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 901–1,000 of 1,006

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  2. ESTRATÉGIAS PARA OTIMIZAR PROCESSOS DE ANOTAÇÃO E GERAÇÃO DE DATASETS DE SEGMENTAÇÃO SEMÂNTICA EM IMAGENS DE MAMOGRAFIA
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  3. Active domain adaptation method for label expansion problem
    Ruicong Zhang, Yu Bao, Weng Qinle, Li Zhongtian, Yonggang Li · 2022 · Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability
  4. TIMS: A Novel Approach for Incrementally Few-Shot Text Instance Selection via Model Similarity
    Tianjie Ju, Han Liao, Gongshen Liu · 2022 · International Joint Conference on Neural Networks (IJCNN)
  5. Active Deep Learning Technique for Underwater Target Recognition
    Jiankun Lyu, L. W. Jiang, Chao Yang, Shijie Wang · 2022 · MTS/IEEE OCEANS Conference (OCEANS)
  6. Efficient Training Method for Point Cloud-Based Object Detection Models by Combining Environmental Transitions and Active Learning
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  7. Query Based Iterative Learning Approach for Lightpath Deployment in Optical Networks
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  8. Preemptively Pruning Clever-Hans Strategies in Deep Neural Networks
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  9. Shiitake Mushroom Semantic Segmentation Method Based on Search Focus Network
    Juan Du, Songxuan Liu · 2023 · International Conference on Automation, Robotics and Applications
  10. Learning to Select Pivotal Samples for Meta Re-weighting
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  11. Active pairwise distance learning for efficient labeling of large datasets by human experts
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  12. ACL: active curriculum learning to reducing label efforts
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  13. Jaxsgmc: Modular Stochastic Gradient MCMC in Jax
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  14. Interactive Span Recommendation for Biomedical Text
    Louis Blankemeier, Theodore Zhao, Robert Tinn, Sid Kiblawi, Yu Gu, Akshay Sanjay Chaudhari, Hoifung Poon, Sheng Zhang, Wei Mu, J. Preston · 2023 · Clinical Natural Language Processing Workshop (ClinicalNLP)
  15. Learning Category Discriminability for Active Domain Adaptation
    Jiali Zhang, Mingkang Li, Wen Zhang, Lu Gong, Zili Zhang · 2023 · Lecture notes in computer science
  16. A Geometrical Characterization on Feature Density of Image Datasets
    Zhen Liang, Changyuan Zhao, Wanwei Liu, Xue Bai, Wenjing Yang · 2023 · IEEE International Conference on Multimedia and Expo (ICME)
  17. The Fourth Workshop on Insights from Negative Results in NLP
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  19. Porting and Optimization of Electric Power Consumers Anomaly Behaviour Monitoring on ARM Platform
    Yujiang Long, Ye Zhong, Wei Wei, Zhu Zhan, Bin Liu · 2023 · International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI)
  20. Active Learning—Review
    KC Santosh, Suprim Nakarmi · 2023 · SpringerBriefs in applied sciences and technology
  21. A Two-Stage Active Learning Algorithm for NLP Based on Feature Mixing
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  22. Discordant pair analysis for sample efficient model evaluation
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  23. Explicit Aspect Annotation via Transfer and Active Learning
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  24. Co-evolving data-driven and NLU-driven Synthesizers for Generating Code in Domain Growth and Data Scarcity
    Jiasheng Gu, Zifan Nan, Zhiyuan Peng, Xipeng Shen, Dongkuan Xu · 2023
  25. Proceedings of the 2nd Workshop on Pattern-based Approaches to NLP in the Age of Deep Learning
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  26. Selective Labeling: How to Radically Lower Data-Labeling Costs for Document Extraction Models
    Yichao Zhou, James B. Wendt, Navneet Potti, Jing Xie, Sandeep Tata · 2023 · Conference on Empirical Methods in Natural Language Processing (EMNLP)
  27. Few Labels are Enough! Semi-supervised Graph Learning for Social Interaction
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  28. Sharing is Caring: Concurrent Interactive Segmentation and Model Training using a Joint Model
    I. A. Mikhailov, Benoît Chauveau, Nicolas Bourdel, Adrien Bartoli · 2023 · IEEE International Conference on Computer Vision Workshops
  29. Active contrastive coding reducing label effort for sensor-based human activity recognition
    Zhixin Li, Hao Liu, Zhan Huan, Jiuzhen Liang · 2023 · Journal of Intelligent & Fuzzy Systems
  30. High Accuracy and Cost-Saving Active Learning: 3D WD-UNet for Airway Segmentation
    Shi‐Yi Wang, Nan Yang, Walsh Simon, Guang Yang · 2023 · International Symposium on Medical Information Processing and Analysis (SIPAIM)
  31. Batch Mode Deep Active Learning for Regression on Graph Data
    Peter Samoaa, Linus Aronsson, Philipp Leitner, Morteza Haghir Chehreghani · 2023 · BigData Congress [Services Society]
  32. Training Efficiency Gains in Data-Driven 2D Airfoil Inverse Design using Active Learning
    Jun Wang, Mark Fuge · 2024 · AIAA SciTech Forum
  33. Dual-Classifier Collaborative Method Based on Semi-Supervised Active Learning
    Baoguo Wei, Xinyu Wang, Yue Zhang, Mingzhi Cai, Xu Li, Lixin Li · 2023 · IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)
  34. Deep Individual Active Learning: Safeguarding against Out-of-Distribution Challenges in Neural Networks
    Shachar Shayovitz, Koby Bibas, M. Feder · 2024 · Entropy
  35. Dynamic Knowledge Expansion: Real-time Text Classification with Deep Convolutional Neural Networks
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  36. A Hybrid Sampling Methodology Based Cost Effective Active Learning for Tabular Data
    Sharath M Shankaranarayana, Anubhab Samal, Chikka Veera Raghavendra, Vijay Sankar, Arindam Dey, Sangam Kumar Singh · 2024 · International Conference on Communication Systems & Networks (COMSNETS)
  37. Anomaly Detection-Aided Active Learning
    Georgii Nigmatulin, Konstantin Pavlov · 2023 · Globecom
  38. Label Smarter, Not Harder: CleverLabel for Faster Annotation of Ambiguous Image Classification with Higher Quality
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  39. ALLFA: Active Learning Through Label and Feature Augmentation
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  40. RETRACTED: Model extraction via active learning by fusing prior and posterior knowledge from unlabeled data
    Lijun Gao, Kai Liu, Wenjun Liu, Jiehong Wu, Jin Xiao · 2024 · Journal of Intelligent & Fuzzy Systems · Retracted
  41. Additional file 1 of scSemiAE: a deep model with semi-supervised learning for single-cell transcriptomics
    Dong, Jiayi, Yin Zhang, Fei Wang · 2022 · Figshare
  42. Additional file 2 of scSemiAE: a deep model with semi-supervised learning for single-cell transcriptomics
    Dong, Jiayi, Yin Zhang, Fei Wang · 2022 · Figshare
  43. Additional file 3 of scSemiAE: a deep model with semi-supervised learning for single-cell transcriptomics
    Dong, Jiayi, Yin Zhang, Fei Wang · 2022 · Figshare
  44. From Principles to Questions: Hybrid Active Learning in Art and Design Practices
    Amic G. Ho · 2024 · Lecture notes in educational technology
  45. بيئة تعليمية لتدريس العلوم قائمة على مداخل تعليم الاستدامة (الخدمي والعميق) لتنمية مهارات تخطيط التحقيقات وتنفيذها والاتجاه نحو التعليم الأخضر لدى تلاميذ المرحلة الابتدائية..
    ابتسام علی أحمد إبراهیم · 2024 · Al-Mağallah Al-ʿilmiyyaẗ Li Kulliyyaẗ Al-Tarbiyyaẗ - Ǧāmiʿaẗ Awadī Al-Ǧadīd/Al-Mağallah Al-ʿilmiyyaẗ Li Kulliyyaẗ Al-Tarbiyyaẗ - Ǧāmiʿaẗ El-Wadī Al-Ǧadīd
  46. A Human-In-One-Loop Active Domain Adaptation Framework for Digit Recognition
    Hao Xiu, Guanchen Li, Jie He, Xiaotong Zhang, Yue Qi · 2024 · Applied Artificial Intelligence
  47. Active Learning Enabled Low-Cost Cell Image Segmentation Using Bounding Box Annotation
    Yu Zhu, Qiang Yang, Li Xu · 2024 · SSRN Electronic Journal
  48. Trust at Hand: A Multi-touch Tabletop Interface for Collaborative Training of Machine Learning Models in the Medical Domain
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  49. Trust at Hand: A Multi-touch Tabletop Interface for Collaborative Training of Machine Learning Models in the Medical Domain
    Alexander Bakogeorge · 2024
  50. Review on scene graph generation methods
    S Monesh, Narayanan Chidambaram Senthilkumar · 2024 · Multiagent and Grid Systems
  51. An Active Learning Semantic Segmentation Model Based on an Improved Double Deep Q-Network
    Yan Yu · 2024 · International Journal on Data Science and Technology
  52. Advancing low resource information extraction and dialogue system using data efficient methods
    Bosheng Ding · 2024
  53. Efficient Stream-Based Active Learning Initialization for Legged Robots Based on a PCA/K-Means Image Selection Approach
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  54. Multi-stage cost-efficient multi-label active learning
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  55. Classifier Guided Cluster Density Reduction for Dataset Selection
    Cheng Chang, Keyu Long, Zijian Li, Himanshu Rai · 2024 · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
  56. MelissaDL x Breed: Towards Data-Efficient On-line Supervised Training of Multi-parametric Surrogates with Active Learning
    Sofya Dymchenko, Abhishek Purandare, Bruno Raffin · 2024 · International Conference for High Performance Computing, Networking, Storage and Analysis (SC)
  57. Boosting Representation Learning via Similarity-based Active Data Sampling from the Web
    Shiryu Ueno, Kunihito Kato · 2024 · International Workshop on Intelligent Systems (IWIS)
  58. Support Vector Machines With Uncertainty Option and Incremental Sampling for Kriging
    Chen Xiong, Paul Honeiné, Maxime Bérar, Antonin Van Exem · 2024 · Expert Systems
  59. Macro-AUC-Driven Active Learning Strategy for Multi-Label Classification Enhancement
    Minghao Li, Junjie Qiu, Weishi Shi · 2024 · IEEE International Conference on Multimedia Information Processing and Retrieval (MIPR)
  60. Active learning for efficient data selection in radio‐signal‐based positioning via deep learning
    Vincent Corlay, Milan Courcoux‐Caro · 2024 · Electronics Letters
  61. Supervised Learning: Classification
    Mauro Castelli, Gloria Pietropolli, Luca Manzoni · 2024 · Elsevier eBooks
  62. Knowledge Distillation in Deep Networks Under a Constrained Query Budget
    Ankita Singh, Shayok Chakraborty · 2024 · Lecture notes in computer science
  63. When Uncertainty-Based Active Learning May Fail?
    Amir Hossein Rahmati, Mingzhou Fan, Ruida Zhou, Nathan M. Urban, Byung-Jun Yoon, Xiaoning Qian · 2024 · Lecture notes in computer science
  64. Soil Class Mapping with Severely Limited Sample Data: A Conceptual Model of Soil-Landscape Relationships in Complex Terrain
    Mingliang Ye, Xiaodong Song, Gan‐Lin Zhang, Chao Li, Yonghui Shi, Chu Zhang, Jun Gu · 2024 · SSRN Electronic Journal
  65. Streamlining Crop Segmentation with Multispectral Imaging and Foundation Models: Minimizing Manual Annotation
    Przemysław Aszkowski, Marek Kraft · 2024 · IEEE International Conference on Intelligent Computer Communication and Processing (ICCP)
  66. Certainly Uncertain: Demystifying ML Uncertainty for Active Learning in Network Monitoring Tasks
    Katharina Dietz, Mehrdad Hajizadeh, Nikolas Wehner, Stefan Geißler, Pedro Casas, Michael Seufert, Tobias Hoßfeld · 2024 · International Conference on Network and Service Management (CNSM)
  67. Active Learning Methods for Training Datasets
    Aritra Raychaudhuri, Vaishnavi Athrey, M R Anala · 2024 · International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS)
  68. CoT based Few-Shot Learning of Negative Comments Filtering
    Takashi Mitadera, Takehito Utsuro · 2024 · IEEE International Conference on Big Data (BigData)
  69. ORIS: Online Active Learning Using Reinforcement Learning-based Inclusive Sampling for Robust Streaming Analytics System
    Rahul Pandey, Ziwei Zhu, Hemant Purohit · 2024 · IEEE International Conference on Big Data (BigData)
  70. A Survey of Validation and Verification Methods for AI-Based Vehicle Functions
    Turgay Aslandere, Umut Durak · 2025 · SAE International Journal of Connected and Automated Vehicles
  71. ActiveConfusion: Efficient Cold-Start Active Learning Using Pretext Task Confusion
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  72. CaCOM: customizing text-to-image diffusion models in the wild via continual active selection
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  73. Machine Fault Diagnosis Based on Probabilistic Bayesian Active Learning
    Liang Zhao, Yuejian Chen · 2024 · Global Reliability and Prognostics and Health Management Conference (PHM)
  74. LG-FAL: Locality-customized GSA Federated Active Learning
    Shuwen Wang, Xingquan Zhu A · 2024 · IEEE International Conference on Knowledge Graph (ICKG)
  75. Likelihood-Weighted Active Selection of Training Data for Improved Extreme Weather Event Prediction in Climate Models
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  76. Speedup of Training Deep Neural Networks in the Streaming Approach Using Genetic Algorithms with an Application of Drift Detection
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  77. Efficient and Accurate Surrogate-Assisted Approach to Multi-objective Optimization Using Deep Neural Networks
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  78. Active Learning Application for Mitosis Detection. A Brief Review.
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  79. Active learning attraction basins of dynamical system
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  80. Time Series-Based Framework for Global Temperature Forecasting Using Fb-Prophet
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  81. Traffic Flow Prediction with Heterogenous Data Using a Hybrid LSTM_BILSTM Model
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  82. Adversarial Example Attacks and Defends on Autopilot Perception System Neural Based on Neural Network: A Survey
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  83. FedRAL: Cost-Effective Distributed Annotation via Federated Reinforced Active Learning
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  84. Active Learning for Image Segmentation with Binary User Feedback
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  85. Diffusion-Based Active Learning for Distributed Client Manifolds
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  86. Hierarchical Multi-Source Uncertainty Aggregation for Interactive Video Captioning
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  87. Integrating Inference and Experimental Design for Contextual Behavioral Model Learning
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  88. Trust Issues in Active Learning and Their Impact on Real-World Applications
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  89. Active Learning Combining Neighborhood Density and Uncertainty
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  90. Active Data Acquisition–An Information Theoretic Approach
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  91. NOOPS: Nonmyopic Feedback-Driven Pattern Search in Multivariate Time Series
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  92. Bidirectional Active Learning for Information Amplification
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