IEEE

MC-NCLWO: Newton’s Cooling Law-Based Oversampling Algorithm for Multi-Class Imbalanced Datasets With Feature Noise

Abstract: Imbalanced data classification remains a fundamental challenge in machine learning, especially in multi-class scenarios where feature noise, class overlap, and small disjunct sub-concepts ...
GitHub

Multi-Agent Debate with Memory Masking

To address this problem, we introduce a simple yet effective multi-agent debate framework, multi-agent debate with memory masking (MAD-M$^2$), to improve the robustness of MAD by allowing LLM agents ...
Frontiers

DenseLes: slice-wise dense network for multiple sclerosis lesion segmentation and classification

Accurate and reliable segmentation of multiple sclerosis (MS) lesions from magnetic resonance imaging (MRI) is essential for diagnosis and monitoring disease progression. Therefore, a robust and ...
IEEE

Deep-EFNet: An Optimized EfficientNetB0 Architecture With Dual Regularization for Scalable Multi-Class Brain Tumor Classification in MRI

Abstract: Brain tumor classification from MRI images plays a crucial role in early diagnosis and treatment planning. While deep learning approaches have shown promise in this domain, achieving high ...