1 code implementation • EMNLP (ClinicalNLP) 2020 • Yifan Peng, SungWon Lee, Daniel C. Elton, Thomas Shen, Yu-Xing Tang, Qingyu Chen, Shuai Wang, Yingying Zhu, Ronald Summers, Zhiyong Lu
We then introduce an end-to-end approach based on the combination of rules and transformer-based methods to detect these abdominal lymph node mentions and classify their types from the MRI radiology reports.
1 code implementation • EMNLP 2021 • Hoang Nguyen, Dong Nie, Taivanbat Badamdorj, Yujie Liu, Yingying Zhu, Jason Truong, Li Cheng
Our paper aims to automate the generation of medical reports from chest X-ray image inputs, a critical yet time-consuming task for radiologists.
no code implementations • 27 Feb 2024 • Hongcheng Yang, Dingkang Liang, Dingyuan Zhang, Zhe Liu, Zhikang Zou, Xingyu Jiang, Yingying Zhu
For such purpose, this paper presents an advanced sampler that achieves both high accuracy and efficiency.
no code implementations • 24 Feb 2024 • Mingkun Yang, Biao Yang, Minghui Liao, Yingying Zhu, Xiang Bai
Scene text recognition (STR) is a challenging task that requires large-scale annotated data for training.
1 code implementation • 21 Feb 2024 • Mingkun Yang, Biao Yang, Minghui Liao, Yingying Zhu, Xiang Bai
By enhancing the alignment between the canonical mask feature and the text feature, the module ensures more effective fusion, ultimately leading to improved recognition performance.
no code implementations • 28 Nov 2023 • Ling Fu, Zijie Wu, Yingying Zhu, Yuliang Liu, Xiang Bai
We contend that one main limitation of existing generation methods is the insufficient integration of foreground text with the background.
no code implementations • 9 Sep 2023 • Haiquan Zhao, Yuan Gao, Yingying Zhu
In this paper, a generalized minimum error with fiducial points criterion (GMEEF) is presented by adopting the Generalized Gaussian Density (GGD) function as kernel.
no code implementations • 6 Sep 2023 • Mengliang Zhang, Xinyue Hu, Lin Gu, Liangchen Liu, Kazuma Kobayashi, Tatsuya Harada, Ronald M. Summers, Yingying Zhu
In this paper, we re-extract disease labels from CXR reports to make them more realistic by considering disease severity and uncertainty in classification.
1 code implementation • 22 Jul 2023 • Xinyue Hu, Lin Gu, Qiyuan An, Mengliang Zhang, Liangchen Liu, Kazuma Kobayashi, Tatsuya Harada, Ronald M. Summers, Yingying Zhu
Given a pair of main and reference images, this task attempts to answer several questions on both diseases and, more importantly, the differences between them.
no code implementations • 10 May 2023 • Xudong Xie, Zhen Zhu, Zijie Wu, Zhiliang Xu, Yingying Zhu
To our knowledge, ours is the first scheme for this challenging task, including model, training, and evaluation.
no code implementations • 19 Feb 2023 • Xinyue Hu, Lin Gu, Kazuma Kobayashi, Qiyuan An, Qingyu Chen, Zhiyong Lu, Chang Su, Tatsuya Harada, Yingying Zhu
Medical visual question answering (VQA) aims to answer clinically relevant questions regarding input medical images.
1 code implementation • 3 Feb 2023 • Yingying Zhu, Hongji Yang, Yuxin Lu, Qiang Huang
To address the above three challenges for cross-view image matching, we propose a new backbone network, named Simple Attention-based Image Geo-localization network (SAIG).
Ranked #2 on Image-Based Localization on VIGOR Cross Area
no code implementations • 3 Nov 2022 • Liangchen Liu, Qiuhong Ke, Chaojie Li, Feiping Nie, Yingying Zhu
In this paper, we formulate a novel clustering model, which exploits the non-negative feature property and, more importantly, incorporates the multi-view information into a unified joint learning framework: the unified multi-view orthonormal non-negative graph based clustering framework (Umv-ONGC).
2 code implementations • 14 Oct 2022 • Xiaoyan Zhang, Gaoyang Tang, Yingying Zhu, Qi Tian
The issue of image haze removal has attracted wide attention in recent years.
no code implementations • 17 Sep 2022 • Zhanyuan Yang, Jinghua Wang, Yingying Zhu
In the meta-training stage, we propose a cross-view episodic training mechanism to perform the nearest centroid classification on two different views of the same episode and adopt a distance-scaled contrastive loss based on them.
no code implementations • 13 Aug 2022 • Xinyue Hu, Lin Gu, Liangchen Liu, Ruijiang Li, Chang Su, Tatsuya Harada, Yingying Zhu
Existing video domain adaption (DA) methods need to store all temporal combinations of video frames or pair the source and target videos, which are memory cost expensive and can't scale up to long videos.
1 code implementation • 5 Aug 2022 • Ziteng Cui, Yingying Zhu, Lin Gu, Guo-Jun Qi, Xiaoxiao Li, Renrui Zhang, Zenghui Zhang, Tatsuya Harada
Image restoration algorithms such as super resolution (SR) are indispensable pre-processing modules for object detection in low quality images.
no code implementations • 18 Jan 2022 • Qiyuan An, Ruijiang Li, Lin Gu, Hao Zhang, Qingyu Chen, Zhiyong Lu, Fei Wang, Yingying Zhu
To evaluate our proposed method's utility and privacy loss, we apply our model on a medical report disease label classification task using two noisy challenging clinical text datasets.
no code implementations • 7 Jan 2022 • Ziteng Cui, Yingying Zhu, Lin Gu, Guo-Jun Qi, Xiaoxiao Li, Peng Gao, Zenghui Zhang, Tatsuya Harada
Image restoration algorithms such as super resolution (SR) are indispensable pre-processing modules for object detection in degraded images.
no code implementations • 2 Dec 2021 • Yifei HUANG, Xiaoxiao Li, Lijin Yang, Lin Gu, Yingying Zhu, Hirofumi Seo, Qiuming Meng, Tatsuya Harada, Yoichi Sato
Then we design a novel Auxiliary Attention Block (AAB) to allow information from SAN to be utilized by the backbone encoder to focus on selective areas.
no code implementations • NeurIPS 2021 • Hongji Yang, Xiufan Lu, Yingying Zhu
In this work, we address the problem of cross-view geo-localization, which estimates the geospatial location of a street view image by matching it with a database of geo-tagged aerial images.
no code implementations • 3 Sep 2021 • Xinwei He, Silin Cheng, Dingkang Liang, Song Bai, Xi Wang, Yingying Zhu
To investigate this, we propose a novel Locality-Aware Point-View Fusion Transformer (LATFormer) for 3D shape retrieval and classification.
1 code implementation • 27 Aug 2021 • Hoang T. N. Nguyen, Dong Nie, Taivanbat Badamdorj, Yujie Liu, Yingying Zhu, Jason Truong, Li Cheng
Our paper focuses on automating the generation of medical reports from chest X-ray image inputs, a critical yet time-consuming task for radiologists.
no code implementations • 2 Jul 2021 • Hongji Yang, Xiufan Lu, Yingying Zhu
In this work, we address the problem of cross-view geo-localization, which estimates the geospatial location of a street view image by matching it with a database of geo-tagged aerial images.
3 code implementations • 16 Feb 2021 • Dingkang Liang, Wei Xu, Yingying Zhu, Yu Zhou
Most regression-based methods utilize convolution neural networks (CNN) to regress a density map, which can not accurately locate the instance in the extremely dense scene, attributed to two crucial reasons: 1) the density map consists of a series of blurry Gaussian blobs, 2) severe overlaps exist in the dense region of the density map.
no code implementations • 9 Nov 2020 • Qingyu Chen, Tiarnan D. L. Keenan, Alexis Allot, Yifan Peng, Elvira Agrón, Amitha Domalpally, Caroline C. W. Klaver, Daniel T. Luttikhuizen, Marcus H. Colyer, Catherine A. Cukras, Henry E. Wiley, M. Teresa Magone, Chantal Cousineau-Krieger, Wai T. Wong, Yingying Zhu, Emily Y. Chew, Zhiyong Lu
The objective was to develop and evaluate the performance of a novel 'M3' deep learning framework on RPD detection.
no code implementations • 19 Jul 2020 • Youbao Tang, Yu-Xing Tang, Yingying Zhu, Jing Xiao, Ronald M. Summers
We introduce an edge prediction module in E$^2$Net and design an edge distance map between liver and tumor boundaries, which is used as an extra supervision signal to train the edge enhanced network.
no code implementations • 14 Jul 2020 • Yingying Zhu, You-Bao Tang, Yu-Xing Tang, Daniel C. Elton, Sung-Won Lee, Perry J. Pickhardt, Ronald M. Summers
We expect the utility of our framework will extend to other problems beyond segmentation due to the improved quality of the generated images and enhanced ability to preserve small structures.
1 code implementation • 11 Jun 2020 • Yifan Peng, Yu-Xing Tang, Sung-Won Lee, Yingying Zhu, Ronald M. Summers, Zhiyong Lu
(1) We show that COVID-19-CT-CXR, when used as additional training data, is able to contribute to improved DL performance for the classification of COVID-19 and non-COVID-19 CT. (2) We collected CT images of influenza and trained a DL baseline to distinguish a diagnosis of COVID-19, influenza, or normal or other types of diseases on CT. (3) We trained an unsupervised one-class classifier from non-COVID-19 CXR and performed anomaly detection to detect COVID-19 CXR.
no code implementations • 22 May 2020 • Yingying Zhu, Daniel C. Elton, SungWon Lee, Perry J. Pickhardt, Ronald M. Summers
In medical imaging applications, preserving small structures is important since these structures can carry information which is highly relevant for disease diagnosis.
no code implementations • MIDL 2019 • Yingying Zhu, Daniel C. Elton, SungWon Lee, Perry J. Pickhardt, Ronald M. Summers
In medical imaging applications, preserving small structures is important since these structures can carry information which is highly relevant for disease diagnosis.
no code implementations • 12 Apr 2019 • Bin Sun, Chen Chen, Yingying Zhu, Jianmin Jiang
The task of cross-view image geo-localization aims to determine the geo-location (GPS coordinates) of a query ground-view image by matching it with the GPS-tagged aerial (satellite) images in a reference dataset.
no code implementations • 1 Aug 2018 • Yingying Zhu, Jiong Wang, Lingxi Xie, Liang Zheng
Visual place recognition is challenging in the urban environment and is usually viewed as a large scale image retrieval task.
1 code implementation • 13 Mar 2018 • Yingying Zhu, Mert R. Sabuncu
An additional layer of complexity is that, in real life, the amount and type of data available for each patient can differ significantly.
no code implementations • CVPR 2014 • Yingying Zhu, Dong Huang, Fernando de la Torre, Simon Lucey
The task of estimating complex non-rigid 3D motion through a monocular camera is of increasing interest to the wider scientific community.
no code implementations • CVPR 2013 • Yingying Zhu, Nandita M. Nayak, Amit K. Roy-Chowdhury
This is motivated from the observations that the activities related in space and time rarely occur independently and can serve as the context for each other.