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SolarPanel Segmentation :Self-Supervised Learning for Imperfect Datasets
The increasing adoption of solar energy necessitates advanced methodologies for monitoring and maintenance to ensure optimal performance of solar panel installations.
ReFuSeg: Regularized Multi-Modal Fusion for Precise Brain Tumour Segmentation
This paper presents a novel multi-modal approach for brain lesion segmentation that leverages information from four distinct imaging modalities while being robust to real-world scenarios of missing modalities, such as T1, T1c, T2, and FLAIR MRI of brains.
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