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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Patel, Vivek K.
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (6/6 displayed)
- 2023A parametric study and experimental investigations of microstructure and mechanical properties of multi-layered structure of metal core wire using wire arc additive manufacturingcitations
- 2023Hybrid perovskites thin films morphology identification by adapting multiscale-SinGAN architecture, heat transfer search optimized feature selection and machine learning algorithmscitations
- 2022Multi-Response Optimization of Al2O3 Nanopowder-Mixed Wire Electrical Discharge Machining Process Parameters of Nitinol Shape Memory Alloycitations
- 2021Parametric Optimization and Effect of Nano-Graphene Mixed Dielectric Fluid on Performance of Wire Electrical Discharge Machining Process of Ni55.8Ti Shape Memory Alloycitations
- 2021Multi-Response Optimization of Abrasive Waterjet Machining of Ti6Al4V Using Integrated Approach of Utilized Heat Transfer Search Algorithm and RSMcitations
- 2021Optimization of Activated Tungsten Inert Gas welding process parameters using heat transfer search algorithm: with experimental validation using case studiescitations
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article
Hybrid perovskites thin films morphology identification by adapting multiscale-SinGAN architecture, heat transfer search optimized feature selection and machine learning algorithms
Abstract
<jats:title>Abstract</jats:title><jats:p>The automation in image analysis while dealing with enormous images generated is imperative to deliver defect-free surfaces in the optoelectronic area. Five distinct morphological images of hybrid perovskites are investigated in this study to analyse and predict the surface properties using machine learning algorithms. Here, we propose a new framework called Multi-Scale-SinGAN to generate multiple morphological images from a single-image. Ten different quality parameters are identified and extracted from each image to select the best features. The heat transfer search is adopted to select the optimized features and compare them with the results obtained using the cuckoo search algorithm. A comparison study with four machine learning algorithms has been evaluated and the results confirms that the features selected through heat transfer search algorithm are effective in identifying thin film morphological images with machine learning models. In particular, ANN-HTS outperforms other combinations : Tree-HTS, KNN-HTS and SVM-HTS, in terms of accuracy,precision, recall and F1-score.</jats:p>