Q Bi, B Zhou, K Qin, Q Ye, GS Xia - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Aerial scene classification remains challenging as: 1) the size of key objects in determining the scene scheme varies greatly and 2) many objects irrelevant to the scene scheme are …
Y Yang, Y Tu, H Lei, W Long - Pattern Recognition, 2023 - Elsevier
Multi-instance learning is common for computer vision tasks, especially in biomedical image processing. Traditional methods for multi-instance learning focus on designing feature …
Learning on sets is increasingly gaining attention in the machine learning community, due to its widespread applicability. Typically, representations over sets are computed by using fixed …
Strongly supervised learning requires detailed knowledge of truth labels at instance levels, and in many machine learning applications, this is a major drawback. Multiple instance …
J Yang, D Tang, J Yu, J Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Ensuring the safety and reliability of unmanned aerial vehicles (UAVs) has become a critical issue as they continue to advance. Analyzing anomalous events using event-based …
M Luo, X Chang, C Gong - Computer Vision and Image Understanding, 2021 - Elsevier
Multimedia event detection is the task of detecting a specific event of interest in an user- generated video on websites. The most fundamental challenge facing this task lies in the …
In Multiple Instance Learning (MIL), models are trained using bags of instances, where only a single label is provided for each bag. A bag label is often only determined by a handful of …
The most prevalent form of bladder cancer is urothelial carcinoma, characterized by a high recurrence rate and substantial lifetime treatment costs for patients. Grading is a prime factor …
B Zhang, J Xue - IET Computer Vision, 2024 - Wiley Online Library
In recent years, the challenge of detecting anomalies in real‐world surveillance videos using weakly supervised data has emerged. Traditional methods, utilising multi‐instance learning …