Cost Splitting for Multi-Objective Conflict-Based Search

no code implementations • 23 Nov 2022 • Cheng Ge, Han Zhang, Jiaoyang Li, Sven Koenig

Our theoretical results show that, when combined with either of these two new splitting strategies, MO-CBS maintains its completeness and optimality guarantees.

Multi-Agent Path Finding

Deep Baseline Network for Time Series Modeling and Anomaly Detection

no code implementations • 10 Sep 2022 • Cheng Ge, Xi Chen, Ming Wang, Jin Wang

By using this deep network, we can easily locate the baseline position and then provide reliable and interpretable anomaly detection result.

Anomaly Detection Time Series Anomaly Detection

DePS: An improved deep learning model for de novo peptide sequencing

no code implementations • 16 Mar 2022 • Cheng Ge, Yi Lu, Jia Qu, Liangxu Xie, Feng Wang, Hong Zhang, Ren Kong, Shan Chang

De novo peptide sequencing from mass spectrometry data is an important method for protein identification.

AbdomenCT-1K: Is Abdominal Organ Segmentation A Solved Problem?

1 code implementation • 28 Oct 2020 • Jun Ma, Yao Zhang, Song Gu, Cheng Zhu, Cheng Ge, Yichi Zhang, Xingle An, Congcong Wang, Qiyuan Wang, Xin Liu, Shucheng Cao, Qi Zhang, Shangqing Liu, Yunpeng Wang, Yuhui Li, Jian He, Xiaoping Yang

With the unprecedented developments in deep learning, automatic segmentation of main abdominal organs seems to be a solved problem as state-of-the-art (SOTA) methods have achieved comparable results with inter-rater variability on many benchmark datasets.

Continual Learning Organ Segmentation +1

Towards Data-Efficient Learning: A Benchmark for COVID-19 CT Lung and Infection Segmentation

2 code implementations • 27 Apr 2020 • Jun Ma, Yixin Wang, Xingle An, Cheng Ge, Ziqi Yu, Jianan Chen, Qiongjie Zhu, Guoqiang Dong, Jian He, Zhiqiang He, Yuntao Zhu, Ziwei Nie, Xiaoping Yang

Purpose: Accurate segmentation of lung and infection in COVID-19 CT scans plays an important role in the quantitative management of patients.

Domain Generalization Few-Shot Learning +5