Mohammad R. Jahanshahi
Orcid: 0000-0001-6583-3087Affiliations:
- Purdue University, Lyle School of Civil Engineering, West Lafayette, IN, USA
According to our database1,
Mohammad R. Jahanshahi
authored at least 19 papers
between 2013 and 2023.
Collaborative distances:
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Bibliography
2023
Deep Learning-Based RGB-D Fusion for Multimodal Condition Assessment of Civil Infrastructure.
J. Comput. Civ. Eng., July, 2023
2022
Deep Learning-Based Building Attribute Estimation from Google Street View Images for Flood Risk Assessment Using Feature Fusion and Task Relation Encoding.
J. Comput. Civ. Eng., 2022
2021
Intelligent IoT systems for civil infrastructure health monitoring: a research roadmap.
Discov. Internet Things, 2021
2020
NB-FCN: Real-Time Accurate Crack Detection in Inspection Videos Using Deep Fully Convolutional Network and Parametric Data Fusion.
IEEE Trans. Instrum. Meas., 2020
ARF-Crack: rotation invariant deep fully convolutional network for pixel-level crack detection.
Mach. Vis. Appl., 2020
J. Comput. Civ. Eng., 2020
2019
Estimating Pavement Roughness by Fusing Color and Depth Data Obtained from an Inexpensive RGB-D Sensor.
Sensors, 2019
Pruning deep convolutional neural networks for efficient edge computing in condition assessment of infrastructures.
Comput. Aided Civ. Infrastructure Eng., 2019
2018
NB-CNN: Deep Learning-Based Crack Detection Using Convolutional Neural Network and Naïve Bayes Data Fusion.
IEEE Trans. Ind. Electron., 2018
Sensors, 2018
Adaptive and Cost-Effective Collection of High-Quality Data for Critical Infrastructure and Emergency Management in Smart Cities - Framework and Challenges.
ACM J. Data Inf. Qual., 2018
2017
Accurate and Robust Scene Reconstruction in the Presence of Misassociated Features for Aerial Sensing.
J. Comput. Civ. Eng., 2017
Int. J. Intell. Robotics Appl., 2017
A texture-Based Video Processing Methodology Using Bayesian Data Fusion for Autonomous Crack Detection on Metallic Surfaces.
Comput. Aided Civ. Infrastructure Eng., 2017
Integrating data information literacy into a service-learning engineering design course.
Proceedings of the 2017 IEEE Frontiers in Education Conference, 2017
2016
Proceedings of the International Conference on Machine Learning and Cybernetics, 2016
2013
An innovative methodology for detection and quantification of cracks through incorporation of depth perception.
Mach. Vis. Appl., 2013
Parametric Performance Evaluation of Wavelet-Based Corrosion Detection Algorithms for Condition Assessment of Civil Infrastructure Systems.
J. Comput. Civ. Eng., 2013
Unsupervised Approach for Autonomous Pavement-Defect Detection and Quantification Using an Inexpensive Depth Sensor.
J. Comput. Civ. Eng., 2013