Molecules are complex dynamic objects that can exist in different molecular forms
(conformations, tautomers, stereoisomers, protonation states, etc.) and often it is not known …

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 …

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 …

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 …

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 …

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 …