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20232026
most citedAutoProSAM: Automated Prompting SAM for 3D Multi-Organ Segmentation

11 citations · 25 across the 12 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.LG2023

FedDRO: Federated Compositional Optimization for Distributionally Robust Learning

Prashant Khanduri, Chengyin Li, Rafi Ibn Sultan +3

Recently, compositional optimization (CO) has gained popularity because of its applications in distributionally robust optimization (DRO) and many other machine learning problems.…

cs.CV2023★ 9 cited

GeoSAM: Fine-tuning SAM with Multi-Modal Prompts for Mobility Infrastructure Segmentation

Rafi Ibn Sultan, Chengyin Li, Hui Zhu +3

In geographical image segmentation, performance is often constrained by the limited availability of training data and a lack of generalizability, particularly for segmenting mobili…

cs.CV2023★ 1 cited

Interpretability-Aware Vision Transformer

Yao Qiang, Chengyin Li, Prashant Khanduri +1

Vision Transformers (ViTs) have become prominent models for solving various vision tasks. However, the interpretability of ViTs has not kept pace with their promising performance.…

cs.CV2023★ 11 cited

AutoProSAM: Automated Prompting SAM for 3D Multi-Organ Segmentation

Chengyin Li, Prashant Khanduri, Yao Qiang +3

Segment Anything Model (SAM) is one of the pioneering prompt-based foundation models for image segmentation and has been rapidly adopted for various medical imaging applications. H…

cs.CV2023★ 1 cited

Fairness-aware Vision Transformer via Debiased Self-Attention

Yao Qiang, Chengyin Li, Prashant Khanduri +1

Vision Transformer (ViT) has recently gained significant attention in solving computer vision (CV) problems due to its capability of extracting informative features and modeling lo…