activity
20162023
most citedHEROHE Challenge: assessing HER2 status in breast cancer without immunohistochemistry or in situ hybridization

53 citations · 254 across the 25 of their papers we have counts for

collaborators

25 papers

cs.CV2023★ 1 cited

Cheap-fake Detection with LLM using Prompt Engineering

Guangyang Wu, Weijie Wu, Xiaohong Liu +3

The misuse of real photographs with conflicting image captions in news items is an example of the out-of-context (OOC) misuse of media. In order to detect OOC media, individuals mu…

cs.CV2022★ 17 cited

Biomedical image analysis competitions: The state of current participation practice

Matthias Eisenmann, Annika Reinke, Vivienn Weru +352

The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known abou…

eess.IV2022

Wound Segmentation with Dynamic Illumination Correction and Dual-view Semantic Fusion

Honghui Liu, Changjian Wang, Kele Xu +4

Wound image segmentation is a critical component for the clinical diagnosis and in-time treatment of wounds. Recently, deep learning has become the mainstream methodology for wound…

cs.CV2022★ 1 cited

Trusted Multi-Scale Classification Framework for Whole Slide Image

Ming Feng, Kele Xu, Nanhui Wu +4

Despite remarkable efforts been made, the classification of gigapixels whole-slide image (WSI) is severely restrained from either the constrained computing resources for the whole…

q-bio.QM2021★ 53 cited

HEROHE Challenge: assessing HER2 status in breast cancer without immunohistochemistry or in situ hybridization

Eduardo Conde-Sousa, João Vale, Ming Feng +15

Breast cancer is the most common malignancy in women, being responsible for more than half a million deaths every year. As such, early and accurate diagnosis is of paramount import…

cs.CV2021★ 4 cited

Multimodal Feature Fusion for Video Advertisements Tagging Via Stacking Ensemble

Qingsong Zhou, Hai Liang, Zhimin Lin +1

Automated tagging of video advertisements has been a critical yet challenging problem, and it has drawn increasing interests in last years as its applications seem to be evident in…

cs.CV2021★ 2 cited

Convolutional Neural Network-Based Age Estimation Using B-Mode Ultrasound Tongue Image

Kele Xu, Tamas Gábor Csapó, Ming Feng

Ultrasound tongue imaging is widely used for speech production research, and it has attracted increasing attention as its potential applications seem to be evident in many differen…

cs.CV2020★ 14 cited

AIM 2020: Scene Relighting and Illumination Estimation Challenge

Majed El Helou, Ruofan Zhou, Sabine Süsstrunk +34

We review the AIM 2020 challenge on virtual image relighting and illumination estimation. This paper presents the novel VIDIT dataset used in the challenge and the different propos…

eess.AS2020★ 2 cited

Quantification of Transducer Misalignment in Ultrasound Tongue Imaging

Tamás Gábor Csapó, Kele Xu

In speech production research, different imaging modalities have been employed to obtain accurate information about the movement and shaping of the vocal tract. Ultrasound is an af…

eess.AS2020★ 21 cited

Audio Tagging by Cross Filtering Noisy Labels

Boqing Zhu, Kele Xu, Qiuqiang Kong +2

High quality labeled datasets have allowed deep learning to achieve impressive results on many sound analysis tasks. Yet, it is labor-intensive to accurately annotate large amount…

cs.MM2020

Multi-Representation Knowledge Distillation For Audio Classification

Liang Gao, Kele Xu, Huaimin Wang +1

As an important component of multimedia analysis tasks, audio classification aims to discriminate between different audio signal types and has received intensive attention due to i…

cs.AI2019

Attention-based Fault-tolerant Approach for Multi-agent Reinforcement Learning Systems

Mingyang Geng, Kele Xu, Yiying Li +3

The aim of multi-agent reinforcement learning systems is to provide interacting agents with the ability to collaboratively learn and adapt to the behavior of other agents. In many…

eess.IV2019★ 4 cited

Denoising convolutional autoencoder based B-mode ultrasound tongue image feature extraction

Bo Li, Kele Xu, Dawei Feng +3

B-mode ultrasound tongue imaging is widely used in the speech production field. However, efficient interpretation is in a great need for the tongue image sequences. Inspired by the…

cs.CV2019★ 3 cited

Predicting tongue motion in unlabeled ultrasound videos using convolutional LSTM neural network

Chaojie Zhao, Peng Zhang, Jian Zhu +3

A challenge in speech production research is to predict future tongue movements based on a short period of past tongue movements. This study tackles speaker-dependent tongue motion…

cs.LG2018★ 12 cited

Learning data augmentation policies using augmented random search

Mingyang Geng, Kele Xu, Bo Ding +2

Previous attempts for data augmentation are designed manually, and the augmentation policies are dataset-specific. Recently, an automatic data augmentation approach, named AutoAugm…

cs.CV2018★ 35 cited

General audio tagging with ensembling convolutional neural network and statistical features

Kele Xu, Boqing Zhu, Qiuqiang Kong +4

Audio tagging aims to infer descriptive labels from audio clips. Audio tagging is challenging due to the limited size of data and noisy labels. In this paper, we describe our solut…

cs.LG2018★ 3 cited

Collaborative Deep Learning Across Multiple Data Centers

Kele Xu, Haibo Mi, Dawei Feng +4

Valuable training data is often owned by independent organizations and located in multiple data centers. Most deep learning approaches require to centralize the multi-datacenter da…

cs.SD2018★ 23 cited

Sample Mixed-Based Data Augmentation for Domestic Audio Tagging

Shengyun Wei, Kele Xu, Dezhi Wang +3

Audio tagging has attracted increasing attention since last decade and has various potential applications in many fields. The objective of audio tagging is to predict the labels of…

cs.SD2018★ 4 cited

Environmental Sound Classification Based on Multi-temporal Resolution Convolutional Neural Network Combining with Multi-level Features

Boqing Zhu, Kele Xu, Dezhi Wang +3

Motivated by the fact that characteristics of different sound classes are highly diverse in different temporal scales and hierarchical levels, a novel deep convolutional neural net…

cs.CV2018★ 1 cited

Sample Dropout for Audio Scene Classification Using Multi-Scale Dense Connected Convolutional Neural Network

Dawei Feng, Kele Xu, Haibo Mi +2

Acoustic scene classification is an intricate problem for a machine. As an emerging field of research, deep Convolutional Neural Networks (CNN) achieve convincing results. In this…

cs.CV2018★ 3 cited

Multi-Scale DenseNet-Based Electricity Theft Detection

Bo Li, Kele Xu, Xiaoyan Cui +3

Electricity theft detection issue has drawn lots of attention during last decades. Timely identification of the electricity theft in the power system is crucial for the safety and…

cs.CV2018★ 7 cited

Mixup-Based Acoustic Scene Classification Using Multi-Channel Convolutional Neural Network

Kele Xu, Dawei Feng, Haibo Mi +5

Audio scene classification, the problem of predicting class labels of audio scenes, has drawn lots of attention during the last several years. However, it remains challenging and f…

cs.CV2017★ 4 cited

Full-reference image quality assessment-based B-mode ultrasound image similarity measure

Kele Xu, Xi Liu, Hengxing Cai +1

During the last decades, the number of new full-reference image quality assessment algorithms has been increasing drastically. Yet, despite of the remarkable progress that has been…

cs.CV2016★ 11 cited

Development of a 3D tongue motion visualization platform based on ultrasound image sequences

Kele Xu, Yin Yang, Aurore Jaumard-Hakoun +5

This article describes the development of a platform designed to visualize the 3D motion of the tongue using ultrasound image sequences. An overview of the system design is given a…