Ruohua Shi — accepted AI-conference papers

2024

Evidential Uncertainty-Guided Mitochondria Segmentation for 3D EM Images

Ruohua Shi, Lingyu Duan, Tiejun Huang, Tingting Jiang

AAAI 2024technical

Recent advances in deep learning have greatly improved the segmentation of mitochondria from Electron Microscopy (EM) images. However, suffering from variations in mitochondrial morphology, imaging conditions, and image noise, existing methods still exhibit high uncertainty in their predictions. Mor…

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2023

OAFormer: Learning Occlusion Distinguishable Feature for Amodal Instance Segmentation

Zhixuan Li, Ruohua Shi, Tiejun Huang, Tingting Jiang

ICASSP 2023accepted

The Amodal Instance Segmentation (AIS) task aims to infer the complete mask of occluded instance. Under many circumstances, existing methods treat occluded objects as unoccluded ones, and vice versa, leading to inaccurate predictions. This is because existing AIS methods do not explicitly utilize th…

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