54 citations · 169 across the 10 of their papers we have counts for
10 papers
Cross-Cancer Knowledge Transfer in WSI-based Prognosis Prediction
Pei Liu, Luping Ji, Jiaxiang Gou +1
Whole-Slide Image (WSI) is an important tool for estimating cancer prognosis. Current studies generally follow a conventional cancer-specific paradigm in which each cancer correspo…
Mining In-distribution Attributes in Outliers for Out-of-distribution Detection
Yutian Lei, Luping Ji, Pei Liu
Out-of-distribution (OOD) detection is indispensable for deploying reliable machine learning systems in real-world scenarios. Recent works, using auxiliary outliers in training, ha…
Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation
Pei Liu, Luping Ji
Uncertainty estimation (UE), as an effective means of quantifying predictive uncertainty, is crucial for safe and reliable decision-making, especially in high-risk scenarios. Exist…
Pseudo-Bag Mixup Augmentation for Multiple Instance Learning-Based Whole Slide Image Classification
Pei Liu, Luping Ji, Xinyu Zhang +1
Given the special situation of modeling gigapixel images, multiple instance learning (MIL) has become one of the most important frameworks for Whole Slide Image (WSI) classificatio…
ProtoDiv: Prototype-guided Division of Consistent Pseudo-bags for Whole-slide Image Classification
Rui Yang, Pei Liu, Luping Ji
Due to the limitations of inadequate Whole-Slide Image (WSI) samples with weak labels, pseudo-bag-based multiple instance learning (MIL) appears as a vibrant prospect in WSI classi…
Shared Coupling-bridge for Weakly Supervised Local Feature Learning
Jiayuan Sun, Jiewen Zhu, Luping Ji
Sparse local feature extraction is usually believed to be of important significance in typical vision tasks such as simultaneous localization and mapping, image matching and 3D rec…
AdvMIL: Adversarial Multiple Instance Learning for the Survival Analysis on Whole-Slide Images
Pei Liu, Luping Ji, Feng Ye +1
The survival analysis on histological whole-slide images (WSIs) is one of the most important means to estimate patient prognosis. Although many weakly-supervised deep learning mode…
DSCA: A Dual-Stream Network with Cross-Attention on Whole-Slide Image Pyramids for Cancer Prognosis
Pei Liu, Bo Fu, Feng Ye +3
The cancer prognosis on gigapixel Whole-Slide Images (WSIs) has always been a challenging task. To further enhance WSI visual representations, existing methods have explored image…
Geometry Attention Transformer with Position-aware LSTMs for Image Captioning
Chi Wang, Yulin Shen, Luping Ji
In recent years, transformer structures have been widely applied in image captioning with impressive performance. For good captioning results, the geometry and position relations o…
Multi-view Subspace Clustering via Partition Fusion
Juncheng Lv, Zhao Kang, Boyu Wang +2
Multi-view clustering is an important approach to analyze multi-view data in an unsupervised way. Among various methods, the multi-view subspace clustering approach has gained incr…