A Survey of Deep Active Learning

Cited by (1,006)

Items 1,001–1,006 of 1,006

  1. Pushing the Boundaries of Mortality Prediction: Advancing High-Risk Sepsis-III Patient Care Through Cutting-Edge Deep Learning Techniques
    Deepak Mahto, Sunil Kumar Singh, Sudhakar Kumar, Manya, Rashmi, Varsha Arya, Kwok Tai Chui, Brij Bhooshan Gupta · 2025 · Lecture notes in networks and systems
  2. Refining Deep Active Learning Pipelines: Leveraging Pseudo-Labeling and Label Calibration for Enhancing Dataset Quality
    Tomoya Kasuga, Gongye Jin, Akira Yuasa, Daria Vazhenina, Narimasa Watanabe · 2025 · International Conference on Computing and Artificial Intelligence (ICCAI)
  3. DDSUD: dynamically detecting subsequence uncertainty and diversity for active learning in imbalanced Chinese sentiment analysis
    Shufeng Xiong, Yibo Si, Guipei Zhang, Bingkun Wang, Guang Zheng, Haiping Si · 2025 · PeerJ Computer Science
  4. Policy Gradient-Based Optimal Subset Selection for Few-Shot Vision-Language Learning
    Muhammad Khizer Ali, Manoranjan Paul, Anwaar Ulhaq, Muhammad Haris Khan, Quazi Mamun · 2025 · Proceedings - International Conference on Image Processing
  5. Learning Nash Equilibrial Hamiltonian for Two-Player Collision-Avoiding Interactions
    Lei Zhang, Siddharth Das, Tanner Merry, Wenlong Zhang, Yi Ren · 2025 · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference
  6. High-resolution remote sensing image classification based on active learning
    Sihang Cheng · 2025 · International Conference on Computer Information and Big Data Applications (CIBDA)