78 citations · 86 across the 6 of their papers we have counts for
9 papers
OcTreeMamba: Topology-Aware Mamba for 3D Medical Segmentation via Octree Sparsification
Kaixiang Mai, Jiaqi Yu, Yuzhu Ji +4
Accurate segmentation of 3D anatomical structures is crucial to medical image analysis. Recently, Mamba-based approaches have achieved promising segmentation performance in capturi…
AOI-Net: Structural Face AOI-Guided Eye-Gaze Track Representation Learning for Autism Spectrum Disorder Detection
Zhanpei Huang, Binbin Sun, Jialiang Chen +5
Eye-movement tracking has emerged as a promising non-invasive approach to Autism Spectrum Disorder (ASD) screening, with systematic differences in attentional allocation and revisi…
Imputation Meets Clustering: Exploiting Latent Subgroup Structure for Missing Data Recovery
Chuyao Zhang, E Li, Taochen Chen +5
Missing data is prevalent in practical applications, making effective imputation an essential preprocessing step for downstream analysis. Real-world datasets often exhibit complex…
Learning Unbiased Cluster Descriptors for Interpretable Imbalanced Concept Drift Detection
Yiqun Zhang, Zhanpei Huang, Mingjie Zhao +5
Unlabeled streaming data are usually collected to describe dynamic systems, where concept drift detection is a vital prerequisite to understanding the evolution of systems. However…
One-Shot Federated Clustering of Non-Independent Completely Distributed Data
Yiqun Zhang, Shenghong Cai, Zihua Yang +3
Federated Learning (FL) that extracts data knowledge while protecting the privacy of multiple clients has achieved remarkable results in distributed privacy-preserving IoT systems,…
TFEC: Multivariate Time-Series Clustering via Temporal-Frequency Enhanced Contrastive Learning
Zexi Tan, Tao Xie, Haoyi Xiao +5
Multivariate Time-Series (MTS) clustering is crucial for signal processing and data analysis. Although deep learning approaches, particularly those leveraging Contrastive Learning…
Stitch the Fragments: One-Shot Hierarchical Federated Clustering
Shenghong Cai, Zihua Yang, Yang Lu +4
Federated Clustering (FC) faces a critical bottleneck in real-world scenarios, i.e., global clusters are rarely intact, often fragmenting into incomplete, multi-granular unlabeled…
One-shot Human Motion Transfer via Occlusion-Robust Flow Prediction and Neural Texturing
Yuzhu Ji, Chuanxia Zheng, Tat-Jen Cham
Human motion transfer aims at animating a static source image with a driving video. While recent advances in one-shot human motion transfer have led to significant improvement in r…
Learning Self-Growth Maps for Fast and Accurate Imbalanced Streaming Data Clustering
Yiqun Zhang, Sen Feng, Pengkai Wang +5
Streaming data clustering is a popular research topic in data mining and machine learning. Since streaming data is usually analyzed in data chunks, it is more susceptible to encoun…