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Kele Xu
Researcher at National University of Defense Technology
Publications - 116
Citations - 1211
Kele Xu is an academic researcher from National University of Defense Technology. The author has contributed to research in topics: Computer science & Convolutional neural network. The author has an hindex of 15, co-authored 89 publications receiving 769 citations. Previous affiliations of Kele Xu include ESPCI ParisTech & Pierre-and-Marie-Curie University.
Papers
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Journal ArticleDOI
Deep Convolutional Neural Network-Based Early Automated Detection of Diabetic Retinopathy Using Fundus Image.
Kele Xu,Dawei Feng,Haibo Mi +2 more
TL;DR: This paper explored the use of deep convolutional neural network methodology for the automatic classification of diabetic retinopathy using color fundus image, and obtained an accuracy of 94.5% on the authors' dataset, outperforming the results obtained by using classical approaches.
Book ChapterDOI
Mixup-Based Acoustic Scene Classification Using Multi-channel Convolutional Neural Network
TL;DR: This paper explores the use of Multi-channel CNN for the classification task, which aims to extract features from different channels in an end-to-end manner, and explores the using of mixup method, which can provide higher prediction accuracy and robustness in contrast with previous models.
Journal ArticleDOI
MoNuSAC2020: A Multi-organ Nuclei Segmentation and Classification Challenge
Ruchika Verma,Neeraj Kumar,Abhijeet Patil,Nikhil Cherian Kurian,Swapnil Rane,Simon Graham,Quoc Dang Vu,Mieke Zwager,Shan E Ahmed Raza,Nasir M. Rajpoot,Xiyi Wu,Huai Chen,Yijie Huang,Lisheng Wang,Hyun Jung,G Thomas Brown,Yanling Liu,Shuolin Liu,Seyed Alireza Fatemi Jahromi,Ali Asghar Khani,Ehsan Montahaei,Mahdieh Soleymani Baghshah,Hamid Behroozi,Pavel Semkin,Alexandr G. Rassadin,Prasad Dutande,Romil Lodaya,Ujjwal Baid,Bhakti Baheti,Sanjay N. Talbar,Amirreza Mahbod,Rupert Ecker,Isabella Ellinger,Zhipeng Luo,Bin Dong,Zhengyu Xu,Yuehan Yao,Shuai Lv,Ming Feng,Kele Xu,Hasib Zunair,Abdessamad Ben Hamza,Steven Smiley,Tang-Kai Yin,Qi-Rui Fang,Shikhar Srivastava,Dwarikanath Mahapatra,Lubomira Trnavska,Hanyun Zhang,Priya Lakshmi Narayanan,Justin Law,Yinyin Yuan,Abhiroop Tejomay,Aditya Mitkari,Dinesh Koka,Vikas Ramachandra,Lata Kini,Amit Sethi +57 more
TL;DR: The MoNuSAC2020 dataset as discussed by the authors contains 46,000 nuclei from 37 hospitals, 71 patients, four organs, and four nucleus types from the International Symposium on Biomedical Imaging.
Proceedings ArticleDOI
NTIRE 2021 Challenge on Perceptual Image Quality Assessment
Jinjin Gu,Haoming Cai,Chao Dong,Jimmy Ren,Yu Qiao,Shuhang Gu,Radu Timofte,Manri Cheon,Sung-Jun Yoon,Byungyeon Kang,Junwoo Lee,Qing Zhang,Haiyang Guo,Bin Yi,Yuqing Hou,Hengliang Luo,Jingyu Guo,Zirui Wang,Hai Wang,Wenming Yang,Qingyan Bai,Shuwei Shi,Weihao Xia,Mingdeng Cao,Jiahao Wang,Yifan Chen,Yujiu Yang,Yang Li,Tao Zhang,Longtao Feng,Yiting Liao,Junlin Li,William Thong,Jose Costa Pereira,Ales Leonardis,Steven McDonagh,Kele Xu,Lehan Yang,Hengxing Cai,Pengfei Sun,Seyed Mehdi Ayyoubzadeh,Ali Royat,Sid Ahmed Fezza,Dounia Hammou,Wassim Hamidouche,Sewoong Ahn,Gwangjin Yoon,Koki Tsubota,Hiroaki Akutsu,Kiyoharu Aizawa +49 more
TL;DR: The NTIRE 2021 challenge on perceptual image quality assessment (IQA) as discussed by the authors was held in conjunction with the New Trends in Image Restoration and Enhancement workshop (NTIRE) workshop at CVPR 2021.
Book ChapterDOI
AIM 2020: Scene Relighting and Illumination Estimation Challenge
Majed El Helou,Ruofan Zhou,Sabine Süsstrunk,Radu Timofte,Mahmoud Afifi,Michael S. Brown,Kele Xu,Hengxing Cai,Yuzhong Liu,Li-Wen Wang,Zhi-Song Liu,Chu-Tak Li,Sourya Dipta Das,Nisarg Shah,Akashdeep Jassal,Tongtong Zhao,Shanshan Zhao,Sabari Nathan,M. Parisa Beham,R. Suganya,Qing Wang,Zhongyun Hu,Xin Huang,Yaning Li,Maitreya Suin,Kuldeep Purohit,A. N. Rajagopalan,Densen Puthussery,P. S. Hrishikesh,Melvin Kuriakose,C. V. Jiji,Yu Zhu,Liping Dong,Zhuolong Jiang,Chenghua Li,Cong Leng,Jian Cheng +36 more
TL;DR: The AIM 2020 challenge on virtual image relighting and illumination estimation as discussed by the authors focused on one-to-one relighting, where the objective was to relight an input photo of a scene with a different color temperature and illuminant orientation.