D-Index & Metrics Best Publications

Mani Golparvar-Fard

University of Illinois at Urbana-Champaign
United States

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name Citations Publications World Ranking National Ranking

Computer Science D-index 38 Citations 6,808 164 World Ranking 6423 National Ranking 3079

Overview

What is he best known for?

The fields of study Mani Golparvar-Fard is best known for:

Computer vision
Civil engineering
Machine learning

In his research, Structural health monitoring is intimately related to Structural engineering, which falls under the overarching field of Building construction. His studies link Structural engineering with Structural health monitoring. As part of the same scientific family, he usually focuses on Construction management, concentrating on Civil engineering and intersecting with Civil infrastructure and Structural element. His Civil infrastructure study frequently links to adjacent areas such as Construction engineering. Mani Golparvar-Fard integrates Construction engineering and Construction management in his studies. His research is interdisciplinary, bridging the disciplines of Civil engineering and Structural element. Mani Golparvar-Fard bridges between several scientific fields such as Architecture and Viewpoints in his study of Visual arts. He performs multidisciplinary studies into Architecture and Building information modeling in his work. Viewpoints connects with themes related to Visual arts in his study.

His most cited work include:

Visual monitoring of civil infrastructure systems via camera-equipped Unmanned Aerial Vehicles (UAVs): a review of related works (311 citations)
Evaluation of image-based modeling and laser scanning accuracy for emerging automated performance monitoring techniques (292 citations)
Automated Progress Monitoring Using Unordered Daily Construction Photographs and IFC-Based Building Information Models (220 citations)

What are the main themes of his work throughout his whole career to date

Mani Golparvar-Fard is involved in relevant fields of research such as Point cloud and Visualization in the domain of Artificial intelligence. His Operating system study has been linked to subjects such as Process (computing) and Schedule. In his research, he performs multidisciplinary study on Process (computing) and Operating system. He applies his multidisciplinary studies on Computer vision and Computer graphics (images) in his research. He merges Computer graphics (images) with Computer vision in his research. He conducted interdisciplinary study in his works that combined Statistics and Data collection. Mani Golparvar-Fard brings together Data collection and Statistics to produce work in his papers. He integrates Human–computer interaction and Augmented reality in his studies. In his works, he performs multidisciplinary study on Augmented reality and Human–computer interaction.

Mani Golparvar-Fard most often published in these fields:

Artificial intelligence (68.12%)
Computer vision (33.33%)
Operating system (33.33%)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Visual monitoring of civil infrastructure systems via camera-equipped Unmanned Aerial Vehicles (UAVs): a review of related works

Youngjib Ham;Kevin K. Han;Jacob J Lin;Mani Golparvar-Fard.
Visualization in Engineering (2016)

408 Citations

Application of D4AR – A 4-Dimensional augmented reality model for automating construction progress monitoring data collection, processing and communication

Mani Golparvar-Fard;Feniosky Peña-Mora;Silvio Savarese.
(2009)

359 Citations

Evaluation of image-based modeling and laser scanning accuracy for emerging automated performance monitoring techniques

Mani Golparvar-Fard;Jeffrey Bohn;Jochen Teizer;Silvio Savarese.
(2011)

354 Citations

Visualization of construction progress monitoring with 4D simulation model overlaid on time-lapsed photographs

Mani Golparvar-Fard;Feniosky Peña-Mora;Carlos A. Arboleda;SangHyun Lee.
(2009)

323 Citations

Automated Progress Monitoring Using Unordered Daily Construction Photographs and IFC-Based Building Information Models

Mani Golparvar-Fard;Feniosky Peña-Mora;Silvio Savarese.
(2015)

304 Citations

Vision-based action recognition of earthmoving equipment using spatio-temporal features and support vector machine classifiers

Mani Golparvar-Fard;Arsalan Heydarian;Juan Carlos Niebles.
Advanced Engineering Informatics (2013)

246 Citations

Automated 2D detection of construction equipment and workers from site video streams using histograms of oriented gradients and colors

Milad Memarzadeh;Mani Golparvar-Fard;Juan Carlos Niebles.
Automation in Construction (2013)

245 Citations

Construction performance monitoring via still images, time-lapse photos, and video streams

Jun Yang;Man-Woo Park;Patricio A. Vela;Mani Golparvar-Fard.
Advanced Engineering Informatics (2015)

215 Citations

Enhancing construction hazard recognition with high-fidelity augmented virtuality

Alex Albert;Matthew R. Hallowell;Brian Kleiner;Ao Chen.
(2014)

202 Citations

Appearance-based material classification for monitoring of operation-level construction progress using 4D BIM and site photologs

Kevin K. Han;Mani Golparvar-Fard.
Automation in Construction (2015)

199 Citations

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Frequent Co-Authors

External Links

Personal Website for Mani Golparvar-Fard