Oral Büyüköztürk

Civil and Structural Engineering · 2004–2018

A researcher in the Science corpus: 10 papers; trusts 170 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Civil and Structural Engineering — 84 citations into it; #689 of 6,160 by trust here, #548 by citations
• Computer Vision and Pattern Recognition — 34 citations into it; #17,157 of 21,575 by trust here, #18,782 by citations
• Building and Construction — 33 citations into it; #763 of 2,909 by trust here, #1,081 by citations
• Materials Chemistry — 25 citations into it
• Artificial Intelligence — 21 citations into it
• Mechanical Engineering — 15 citations into it; #6,171 of 8,300 by trust here, #4,353 by citations
• Mechanics of Materials — 12 citations into it
• Statistics and Probability — 12 citations into it

Whom Oral Büyüköztürk trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. S. Plimpton
2. Jacob Fish
3. James L. Beck
4. Ronald E. Miller
5. Alessandro Laio
6. Ching Au
7. Markus J. Buehler
8. Ka-Veng Yuen
9. Scott T. Smith
10. T. Ackbarow

Who trusts Oral Büyüköztürk overall

1. Denvid Lau
2. Ao Zhou
3. Billie F. Spencer Jr.
4. Young-Jin Cha
5. Yuqing Gao
6. Lik-ho Tam
7. Wooram Choi
8. Shengyuan Li
9. Sattar Dorafshan
10. Zechuan Yu

Papers from Oral Büyüköztürk's perspective

Ordered by how strongly the researchers Oral Büyüköztürk trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet Large Scale Visual Recognition Challenge
7. ImageNet: A large-scale hierarchical image database
8. Attention is All you Need (Neural Information Processing Systems)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Output-only computer vision based damage detection using phase-based optical flow and unscented Kalman filters (2017) — 190 citations
• Optimal sensor placement in structural health monitoring using discrete optimization (2015) — 143 citations
• Autonomous Structural Visual Inspection Using Region‐Based Deep Learning for Detecting Multiple Damage Types (2018) — 1,419 citations
• Use of silica fume and natural volcanic ash as a replacement to Portland cement: Micro and pore structural investigation using NMR, XRD, FTIR and X-ray microtomography (2018) — 193 citations
• Deep Learning‐Based Crack Damage Detection Using Convolutional Neural Networks (2017) — 2,960 citations
• Probabilistic updating of building models using incomplete modal data (2016) — 80 citations
• Structural solution using molecular dynamics: Fundamentals and a case study of epoxy-silica interface (2011) — 175 citations
• Fracture characterization of concrete/epoxy interface affected by moisture (2010) — 166 citations
• Peel and Shear Fracture Characterization of Debonding in FRP Plated Concrete Affected by Moisture (2006) — 139 citations
• Progress on understanding debonding problems in reinforced concrete and steel members strengthened using FRP composites (2004) — 458 citations