CASIA at SemEval-2022 Task 11: Chinese Named Entity Recognition for Complex and Ambiguous Entities

no code implementations • SemEval (NAACL) 2022 • Jia Fu, Zhen Gan, Zhucong Li, Sirui Li, Dianbo Sui, Yubo Chen, Kang Liu, Jun Zhao

This paper describes our approach to develop a complex named entity recognition system in SemEval 2022 Task 11: MultiCoNER Multilingual Complex Named Entity Recognition, Track 9 - Chinese.

Chinese Named Entity Recognition Data Augmentation +3

CASIA@SMM4H’22: A Uniform Health Information Mining System for Multilingual Social Media Texts

no code implementations • SMM4H (COLING) 2022 • Jia Fu, Sirui Li, Hui Ming Yuan, Zhucong Li, Zhen Gan, Yubo Chen, Kang Liu, Jun Zhao, Shengping Liu

This paper presents a description of our system in SMM4H-2022, where we participated in task 1a, task 4, and task 6 to task 10.

named-entity-recognition Named Entity Recognition +1

Multi-Center Fetal Brain Tissue Annotation (FeTA) Challenge 2022 Results

no code implementations • 8 Feb 2024 • Kelly Payette, Céline Steger, Roxane Licandro, Priscille de Dumast, Hongwei Bran Li, Matthew Barkovich, Liu Li, Maik Dannecker, Chen Chen, Cheng Ouyang, Niccolò McConnell, Alina Miron, Yongmin Li, Alena Uus, Irina Grigorescu, Paula Ramirez Gilliland, Md Mahfuzur Rahman Siddiquee, Daguang Xu, Andriy Myronenko, Haoyu Wang, Ziyan Huang, Jin Ye, Mireia Alenyà, Valentin Comte, Oscar Camara, Jean-Baptiste Masson, Astrid Nilsson, Charlotte Godard, Moona Mazher, Abdul Qayyum, Yibo Gao, Hangqi Zhou, Shangqi Gao, Jia Fu, Guiming Dong, Guotai Wang, ZunHyan Rieu, HyeonSik Yang, Minwoo Lee, Szymon Płotka, Michal K. Grzeszczyk, Arkadiusz Sitek, Luisa Vargas Daza, Santiago Usma, Pablo Arbelaez, Wenying Lu, WenHao Zhang, Jing Liang, Romain Valabregue, Anand A. Joshi, Krishna N. Nayak, Richard M. Leahy, Luca Wilhelmi, Aline Dändliker, Hui Ji, Antonio G. Gennari, Anton Jakovčić, Melita Klaić, Ana Adžić, Pavel Marković, Gracia Grabarić, Gregor Kasprian, Gregor Dovjak, Milan Rados, Lana Vasung, Meritxell Bach Cuadra, Andras Jakab

The FeTA Challenge 2022 was able to successfully evaluate and advance generalizability of multi-class fetal brain tissue segmentation algorithms for MRI and it continues to benchmark new algorithms.

Brain Segmentation Segmentation +1

SegRap2023: A Benchmark of Organs-at-Risk and Gross Tumor Volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma

1 code implementation • 15 Dec 2023 • Xiangde Luo, Jia Fu, Yunxin Zhong, Shuolin Liu, Bing Han, Mehdi Astaraki, Simone Bendazzoli, Iuliana Toma-Dasu, Yiwen Ye, Ziyang Chen, Yong Xia, Yanzhou Su, Jin Ye, Junjun He, Zhaohu Xing, Hongqiu Wang, Lei Zhu, Kaixiang Yang, Xin Fang, Zhiwei Wang, Chan Woong Lee, Sang Joon Park, Jaehee Chun, Constantin Ulrich, Klaus H. Maier-Hein, Nchongmaje Ndipenoch, Alina Miron, Yongmin Li, Yimeng Zhang, Yu Chen, Lu Bai, Jinlong Huang, Chengyang An, Lisheng Wang, Kaiwen Huang, Yunqi Gu, Tao Zhou, Mu Zhou, Shichuan Zhang, Wenjun Liao, Guotai Wang, Shaoting Zhang

The precise delineation of Gross Tumor Volumes (GTVs) and Organs-At-Risk (OARs) is crucial in radiation treatment, directly impacting patient prognosis.

Computed Tomography (CT) Image Segmentation +3

Component attention network for multimodal dance improvisation recognition

1 code implementation • 24 Aug 2023 • Jia Fu, Jiarui Tan, Wenjie Yin, Sepideh Pashami, Mårten Björkman

Motion analysis of improvised dance can be challenging due to its unique dynamics.

UM-CAM: Uncertainty-weighted Multi-resolution Class Activation Maps for Weakly-supervised Fetal Brain Segmentation

no code implementations • 20 Jun 2023 • Jia Fu, Tao Lu, Shaoting Zhang, Guotai Wang

To this end, we propose a novel weakly-supervised method with image-level labels based on semantic features and context information exploration.

Brain Segmentation Weakly supervised segmentation

Semantic Segmentation of Panoramic Images Using a Synthetic Dataset

1 code implementation • 2 Sep 2019 • Yuanyou Xu, Kaiwei Wang, Kailun Yang, Dongming Sun, Jia Fu

In addition, it has been shown that by using panoramic images with a 180 degree FoV as training data the model has better performance.

Segmentation Semantic Segmentation