Recent advances in convolutional neural networks
Jiuxiang Gu,Zhenhua Wang,Jason Kuen,Lianyang Ma,Amir Shahroudy,Bing Shuai,Ting Liu,Xingxing Wang,Gang Wang,Jianfei Cai,Tsuhan Chen +10 more
TLDR
A broad survey of the recent advances in convolutional neural networks can be found in this article, where the authors discuss the improvements of CNN on different aspects, namely, layer design, activation function, loss function, regularization, optimization and fast computation.About:
This article is published in Pattern Recognition.The article was published on 2018-05-01 and is currently open access. It has received 3125 citations till now. The article focuses on the topics: Deep learning & Convolutional neural network.read more
Citations
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Journal ArticleDOI
Damage detection in girder bridges using modal curvatures gapped smoothing method and Convolutional Neural Network: Application to Bo Nghi bridge
Duong Huong Nguyen,Duong Huong Nguyen,Quoc Bao Nguyen,Thanh Bui-Tien,Guido De Roeck,Magd Abdel Wahab +5 more
TL;DR: This paper addresses a damage detection method based on changes in modal curvature combined with Convolutional Neural Network and indicates that the combination of GSM and CNN can be used for damage detection and localization.
Journal ArticleDOI
Design of deep ensemble classifier with fuzzy decision method for biomedical image classification
TL;DR: In this paper, a fuzzy min-max model is used to avoid uncertainty and the ensemble output from the base classifiers is fed to the fuzzy model in terms of class probability and labels.
Journal ArticleDOI
Prediction of combustion state through a semi-supervised learning model and flame imaging
TL;DR: A novel semi-supervised learning model integrating denoising autoencoder (DAE), generative adversarial network (GAN) and Gaussian process classifier (GPC) is presented, suggesting that the proposed model provides better prediction accuracy and robustness capability compared to other traditional prediction models.
Journal ArticleDOI
Deep learning-enabled pelvic ultrasound images for accurate diagnosis of ovarian cancer in China: a retrospective, multicentre, diagnostic study.
Yue Gao,Shaoqing Zeng,Xiaoyan Xu,Huayi Li,Shuzhong Yao,Kun Song,Xiao Lin,Lingxi Chen,Junying Tang,Hui Xing,Zhiying Yu,Qinghua Zhang,Shu′e Zeng,Cunjian Yi,H. Xie,Xiaoming Xiong,Guangyao Cai,Zhi Wang,Yuan Wu,Jianhua Chi,Xiaofei Jiao,Yan Qin,Xiaogang Mao,Yu Chen,Xin Jin,Qingqing Mo,Pingbo Chen,Yi Huang,Yushuang Shi,Junmei Wang,Yimin Zhou,Shuping Ding,Sha Zhu,Xin Liu,Xiangyi Dong,Liang Cheng,Lin-lin Zhu,Huanhuan Cheng,Lily Myung-Jin Cha,Yan-zhou Hao,Chunchun Jin,Lei Zhang,Peng Zhou,Meng Sun,Qing Feng Xu,Kehua Chen,Zeyan Gao,Xu Zhang,Yuanyuan Ma,Yang Liu,Li Xiao,Li Xu,L. Peng,Zheyu Hao,Mi Yang,Yane Wang,Hongping Ou,Yongmei Jia,Lihua Tian,Wei Zhang,Ping Jin,Xun Tian,Lei Huang,Zhen Wang,Jiahao Liu,T.Y. Fang,Dan Yan,Heng-Chang Cao,Jingjing Ma,Xiaoting Li,Xuejiao Zheng,Hua Lou,Chunyan Song,Ruyuan Li,Siyuan Wang,Wenqian Li,Xulei Zheng,Guannan Li,Ruqi Chen,Cheng Xu,Ruidi Yu,Ji Wang,Sen Xu,Beihua Kong,Xingyu Xie,Ding Ma,Qinglei Gao +86 more
TL;DR: Wang et al. as mentioned in this paper developed a deep convolutional neural network (DCNN) model that automates evaluation of ultrasound images and to facilitate a more accurate diagnosis of ovarian cancer than existing methods.
Journal ArticleDOI
Temporal deep learning architecture for prediction of COVID-19 cases in India
TL;DR: In this paper , the authors designed the recurrent and convolutional neural network models (RNNs) for predicting the COVID-19 outbreak dynamic trends that may slow down or stop the pandemic.
References
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Gradient-based learning applied to document recognition
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