3 citations · 7 across the 6 of their papers we have counts for
8 papers
On-the-Fly Data Augmentation for Brain Tumor Segmentation
Ishika Jain, Siri Willems, Steven Latre +1
Robust segmentation across both pre-treatment and post-treatment glioma scans can be helpful for consistent tumor monitoring and treatment planning. BraTS 2025 Task 1 addresses thi…
Increasing the Diversity in RGB-to-Thermal Image Translation for Automotive Applications
Kaili Wang, Leonardo Ravaglia, Roberto Longo +5
Thermal imaging in Advanced Driver Assistance Systems (ADAS) improves road safety with superior perception in low-light and harsh weather conditions compared to traditional RGB cam…
Modality Invariant Multimodal Learning to Handle Missing Modalities: A Single-Branch Approach
Muhammad Saad Saeed, Shah Nawaz, Muhammad Zaigham Zaheer +6
Multimodal networks have demonstrated remarkable performance improvements over their unimodal counterparts. Existing multimodal networks are designed in a multi-branch fashion that…
Chameleon: Images Are What You Need For Multimodal Learning Robust To Missing Modalities
Muhammad Irzam Liaqat, Shah Nawaz, Muhammad Zaigham Zaheer +5
Multimodal learning has demonstrated remarkable performance improvements over unimodal architectures. However, multimodal learning methods often exhibit deteriorated performances i…
An In-Depth Analysis of Discretization Methods for Communication Learning using Backpropagation with Multi-Agent Reinforcement Learning
Astrid Vanneste, Simon Vanneste, Kevin Mets +3
Communication is crucial in multi-agent reinforcement learning when agents are not able to observe the full state of the environment. The most common approach to allow learned comm…
Scalability of Message Encoding Techniques for Continuous Communication Learned with Multi-Agent Reinforcement Learning
Astrid Vanneste, Thomas Somers, Simon Vanneste +4
Many multi-agent systems require inter-agent communication to properly achieve their goal. By learning the communication protocol alongside the action protocol using multi-agent re…
Structured Exploration Through Instruction Enhancement for Object Navigation
Matthias Hutsebaut-Buysse, Kevin Mets, Tom De Schepper +1
Finding an object of a specific class in an unseen environment remains an unsolved navigation problem. Hence, we propose a hierarchical learning-based method for object navigation.…
An Analysis of Discretization Methods for Communication Learning with Multi-Agent Reinforcement Learning
Astrid Vanneste, Simon Vanneste, Kevin Mets +4
Communication is crucial in multi-agent reinforcement learning when agents are not able to observe the full state of the environment. The most common approach to allow learned comm…