T
Tuan D. Pham
Researcher at Prince Mohammad bin Fahd University
Publications - 401
Citations - 5458
Tuan D. Pham is an academic researcher from Prince Mohammad bin Fahd University. The author has contributed to research in topics: Fuzzy logic & Image segmentation. The author has an hindex of 30, co-authored 352 publications receiving 4263 citations. Previous affiliations of Tuan D. Pham include Massey University & Cornell University.
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Fuzzy Algorithms: With Applications to Image Processing and Pattern Recognition
Zheru Chi,Hong Yan,Tuan D. Pham +2 more
TL;DR: Fuzzy rules and defuzzification: rules based on experience learning from examples decision tree approach neural network approach minimization of fuzzy rulesdefuzzification and optimization applications concluding remarks.
Journal ArticleDOI
DUNet: A deformable network for retinal vessel segmentation
TL;DR: Wang et al. as discussed by the authors proposed Deformable U-Net (DUNet), which exploits the retinal vessels' local features with a U-shape architecture, in an end-to-end manner for retinal vessel segmentation.
Journal ArticleDOI
Crowdsourcing the creation of image segmentation algorithms for connectomics
Ignacio Arganda-Carreras,Srinivas C. Turaga,Daniel R. Berger,Dan Ciresan,Alessandro Giusti,Luca Maria Gambardella,Jürgen Schmidhuber,Dmitry Laptev,Sarvesh Dwivedi,Joachim M. Buhmann,Ting Liu,Mojtaba Seyedhosseini,Tolga Tasdizen,Lee Kamentsky,Radim Burget,Vaclav Uher,Xiao Tan,Changming Sun,Tuan D. Pham,Erhan Bas,Mustafa Gökhan Uzunbas,Albert Cardona,Johannes Schindelin,H. Sebastian Seung +23 more
TL;DR: In this paper, the first international challenge on 2D segmentation of electron microscopic (EM) images of the brain was organized, and participants submitted boundary maps predicted for a test set of images, and were scored based on their agreement with ground truth from human experts.
Crowdsourcing the creation of image segmentation algorithms for connectomics
Ignacio Arganda-Carreras,Srinivas C. Turaga,Daniel R. Berger,Dan Ciresan,Alessandro Giusti,Luca Maria Gambardella,Jürgen Schmidhuber,Dmitry Laptev,Sarvesh Dwivedi,Joachim M. Buhmann,Ting Liu,Mojtaba Seyedhosseini,Tolga Tasdizen,Lee Kamentsky,Radim Burget,Vaclav Uher,Xiao Tan,Changming Sun,Tuan D. Pham,Erhan Bas,Mustafa Gökhan Uzunbas,Albert Cardona,Johannes Schindelin,H. Sebastian Seung +23 more
TL;DR: In this article, the first international challenge on 2D segmentation of electron microscopic (EM) images of the brain was organized, and participants submitted boundary maps predicted for a test set of images, and were scored based on their agreement with ground truth from human experts.
Journal ArticleDOI
Classification of COVID-19 chest X-rays with deep learning: new models or fine tuning?
TL;DR: AlexNet, GoogleNet, and SqueezeNet require the least training time among pretrained DL models, but with suitable selection of training parameters, excellent classification results can be achieved without data augmentation by these networks.