Assessing the Feasibility of Utilising Convolutional Neural Networks for the Detection of Cracks in Solar Cells

Sharmarke Hassan; Mahmoud Dhimish

Assessing the Feasibility of Utilising Convolutional Neural Networks for the Detection of Cracks in Solar Cells

Electronic Engineering

Research output: Contribution to conference › Poster › peer-review

Original language	English
Publication status	Accepted/In press - 26 Apr 2023
Event	The 17th Photovoltaics Science, Applications and Technology (PVSAT-17 & SuperSolar) Conference - Institute of Physics (IOP), London, United Kingdom Duration: 26 Jun 2023 → 28 Jun 2023 https://iop.eventsair.com/pvsat17/

Conference

Conference	The 17th Photovoltaics Science, Applications and Technology (PVSAT-17 & SuperSolar) Conference
Country/Territory	United Kingdom
City	London
Period	26/06/23 → 28/06/23
Internet address	https://iop.eventsair.com/pvsat17/

Access to Document

IoP PosterAccepted author manuscript, 1.23 MB

Artificial Intelligence-Backed Automation for Detecting Cracks in Solar Cells
Dhimish, M. & Hassan, S.
3/10/22 → 30/09/25
Project: Research project (funded) › Studentship (departmental)

Cite this

@conference{36eb30fabcde4107a8434bf644c766e8,

title = "Assessing the Feasibility of Utilising Convolutional Neural Networks for the Detection of Cracks in Solar Cells",

author = "Sharmarke Hassan and Mahmoud Dhimish",

year = "2023",

month = apr,

day = "26",

language = "English",

note = "The 17th Photovoltaics Science, Applications and Technology (PVSAT-17 & SuperSolar) Conference ; Conference date: 26-06-2023 Through 28-06-2023",

url = "https://iop.eventsair.com/pvsat17/",

}

Assessing the Feasibility of Utilising Convolutional Neural Networks for the Detection of Cracks in Solar Cells. / Hassan, Sharmarke; Dhimish, Mahmoud.
2023. Poster session presented at The 17th Photovoltaics Science, Applications and Technology (PVSAT-17 & SuperSolar) Conference , London, United Kingdom.

Research output: Contribution to conference › Poster › peer-review

Assessing the Feasibility of Utilising Convolutional Neural Networks for the Detection of Cracks in Solar Cells

Conference

Access to Document

Projects

Artificial Intelligence-Backed Automation for Detecting Cracks in Solar Cells

Cite this