Ehsan Mohseni

Ehsan Mohseni

University of Strathclyde

H-index: 10

Europe-United Kingdom

About Ehsan Mohseni

Ehsan Mohseni, With an exceptional h-index of 10 and a recent h-index of 10 (since 2020), a distinguished researcher at University of Strathclyde, specializes in the field of Non-destructive testing and evaluation.

His recent articles reflect a diverse array of research interests and contributions to the field:

Towards an in-process ultrasonic phased array inspection method for narrow-gap welds

A study of machine learning object detection performance for phased array ultrasonic testing of carbon fibre reinforced plastics

Unsupervised machine learning for flaw detection in automated ultrasonic testing of carbon fibre reinforced plastic composites

Golay-based total focusing method using a high-frequency, lead-free, flexible ultrasonic array to improve industrial inspections

3-Dimensional residual neural architecture search for ultrasonic defect detection

A comparison of methods for generating synthetic training data for domain adaption of deep learning models in ultrasonic non-destructive evaluation

Automated multi-modal in-process non-destructive evaluation of wire+ arc additive manufacturing

GANs and alternative methods of synthetic noise generation for domain adaption of defect classification of Non-destructive ultrasonic testing

Ehsan Mohseni Information

University

Position

Lecturer Centre for Ultrasound Engineering (CUE)

Citations(all)

425

Citations(since 2020)

421

Cited By

76

hIndex(all)

10

hIndex(since 2020)

10

i10Index(all)

10

i10Index(since 2020)

10

Email

University Profile Page

Google Scholar

Ehsan Mohseni Skills & Research Interests

Non-destructive testing and evaluation

Top articles of Ehsan Mohseni

Towards an in-process ultrasonic phased array inspection method for narrow-gap welds

NDT & E International

2024/6/1

A study of machine learning object detection performance for phased array ultrasonic testing of carbon fibre reinforced plastics

NDT & E International

2024/6/1

Unsupervised machine learning for flaw detection in automated ultrasonic testing of carbon fibre reinforced plastic composites

Ultrasonics

2024/4/6

Golay-based total focusing method using a high-frequency, lead-free, flexible ultrasonic array to improve industrial inspections

2024/1/17

3-Dimensional residual neural architecture search for ultrasonic defect detection

IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control

2024/1/12

Ehsan Mohseni
Ehsan Mohseni

H-Index: 5

A comparison of methods for generating synthetic training data for domain adaption of deep learning models in ultrasonic non-destructive evaluation

NDT & E International

2024/1/1

Ehsan Mohseni
Ehsan Mohseni

H-Index: 5

Automated multi-modal in-process non-destructive evaluation of wire+ arc additive manufacturing

2023/6/5

GANs and alternative methods of synthetic noise generation for domain adaption of defect classification of Non-destructive ultrasonic testing

arXiv preprint arXiv:2306.01469

2023/6/2

Ehsan Mohseni
Ehsan Mohseni

H-Index: 5

Towards automated in-process NDE of high-value safety critical components built using metal additive manufacturing

2023/4/26

Application of machine learning techniques for defect detection, localisation, and sizing in ultrasonic testing of carbon fibre reinforced polymers

BINDT Aerospace Event 2023

2023/4/25

Ehsan Mohseni
Ehsan Mohseni

H-Index: 5

Mapping SEARCH capabilities to Spirit AeroSystems NDE and automation demand for composites

2023/4/25

Ehsan Mohseni
Ehsan Mohseni

H-Index: 5

Transforming industrial manipulators via kinesthetic guidance for automated inspection of complex geometries

Sensors

2023/4/5

Dual-tandem phased array method for imaging of near-vertical defects in narrow-gap welds

NDT & E International

2023/4/1

In-process non-destructive evaluation of metal additive manufactured components at build using ultrasound and eddy-current approaches

2023/12/1

Eddy currents and ultrasonic testing data fusion for Wire+ Arc Additive Manufacturing

2023/9/13

Application of eddy currents for inspection of carbon fibre composites

2023/9/13

Considerations for process to part inspection for flexible manufacturing NDT

2023/9/13

Using neural architecture search to discover a convolutional neural network to detect defects From volumetric ultrasonic testing data of composites

2023/9/12

Gareth Pierce
Gareth Pierce

H-Index: 18

Ehsan Mohseni
Ehsan Mohseni

H-Index: 5

Ultrasound B-scan defect detection in carbon fibre-reinforced plastic composites with NDT machine learning algorithms

2023/9/12

Data fusion for multi-modal in-process non-destructive evaluation of Wire+ Arc Additive Manufacturing

2023/9/6

See List of Professors in Ehsan Mohseni University(University of Strathclyde)

Co-Authors

academic-engine