A. Gholipour
Computer Vision and Pattern Recognition · 2007–2021
A researcher in the Science corpus: 11 papers; trusts 314 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 136 citations into it; #17,744 of 21,575 by trust here, #12,419 by citations
- Materials Chemistry — 102 citations into it; #4,510 of 11,513 by trust here, #7,794 by citations
- Artificial Intelligence — 95 citations into it; #23,409 of 35,345 by trust here, #18,586 by citations
- Mechanics of Materials — 72 citations into it; #2,876 of 6,291 by trust here, #2,227 by citations
- Radiology, Nuclear Medicine and Imaging — 56 citations into it; #1,420 of 3,265 by trust here, #1,970 by citations
- Atomic and Molecular Physics, and Optics — 52 citations into it; #4,888 of 7,135 by trust here, #5,460 by citations
- Biomedical Engineering — 22 citations into it
- Electrical and Electronic Engineering — 20 citations into it
Whom A. Gholipour trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Mark Jenkinson
- Daniel Rueckert
- Michael Elad
- Geoffrey E. Hinton
- Josien P. W. Pluim
- John C. Mazziotta
- Erik H. W. Meijering
- Mergen H. Ghayesh
- Diederik P. Kingma
- Kaiming He
Who trusts A. Gholipour overall
- Mergen H. Ghayesh
- Seyed Sadegh Mohseni Salehi
- Enzo Ferrante
- Shadab Khan
- Maria Murgasova
- Hamed Farokhi
- Ali Farajpour
- Nikos Paragios
- Deniz Erdoğmuş
- Arvid Lundervold
Papers from A. Gholipour's perspective
Ordered by how strongly the researchers A. Gholipour trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Nonlinear oscillations of viscoelastic microplates (2017) — 48 citations
- Nonlinear oscillations of functionally graded microplates (2018) — 140 citations
- Oscillations of functionally graded microbeams (2017) — 138 citations
- In-plane and out-of-plane nonlinear size-dependent dynamics of microplates (2015) — 211 citations
- Brain charts for the human lifespan (2021) — 1,503 citations
- Deep learning with noisy labels: exploring techniques and remedies in medical image analysis (2019) — 691 citations
- Real-time Deep Pose Estimation with Geodesic Loss for Image-to-Template Rigid Registration (2018) — 123 citations
- A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth (2017) — 339 citations
- Tversky Loss Function for Image Segmentation Using 3D Fully Convolutional Deep Networks (2017) — 1,143 citations
- Robust Super-resolution Volume Reconstruction from Slice Acquisitions: Application to Fetal Brain MRI (2010) — 366 citations
- Brain Functional Localization: A Survey of Image Registration Techniques (2007) — 306 citations