Persoonlijk profiel
Research profile
Mohammad Karami is a Professional Doctorate In Engineering (PDEng) Candidate at the Technical University of Eindhoven, Department of Electrical Engeenirg, Electronic System group. He is mainly focused on developing a print artifact detection system based on Deep Learning Anomaly Detection (DLAD) methods. He aims to develop a highly-accurate optimized deep learning artifact detection system that can perform in real-time, assuring that any visible artifacts within the prints are detected, and the compensation process conducted before the print leaves the printer. His project covers the research and design process from the high level of abstraction to the low level of abstraction.
Expertise gerelateerd aan duurzame ontwikkelingsdoelstellingen van de VN
In 2015 stemden de VN-lidstaten in met 17 wereldwijde duurzame ontwikkelingsdoelstellingen (Sustainable Development Goals, SDG's) om armoede te beëindigen, de planeet te beschermen en voor iedereen welvaart te garanderen. Het werk van deze persoon draagt bij aan de volgende duurzame ontwikkelingsdoelstelling(en):
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SDG 3 – Goede gezondheid en welzijn
Vingerafdruk
- 1 Soortgelijke profielen
Projecten
- 1 Afgelopen
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TTW P16-25 (Project 1): Deep Learning as a Service (DLaaS)
Stuijk, S. (Project Manager), Hosseinibijikola, S. (Projectmedewerker), van der Hagen, D. (Project communicatie medewerker), de Mol-Regels, M. (Project communicatie medewerker) & Karami, S. (Projectmedewerker)
1/01/19 → 31/12/23
Project: Onderzoek direct
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Real-time Print Anomaly Detection Using Deep Neural Networks
Karami, M. H., 9 nov. 2023, Eindhoven: Technische Universiteit Eindhoven.Onderzoeksoutput: Scriptie › EngD Thesis
Open AccessBestand44 Downloads (Pure) -
A Deep Convolutional Neural Network for Melanoma Recognition in Dermoscopy Images
Haghighi, S. N., Danyali, H., Helfroush, M. S. & Karami, M. H., 31 dec. 2020, 2020 10th International Conference on Computer and Knowledge Engineering (ICCKE). Institute of Electrical and Electronics Engineers, blz. 453-456 4 blz. 9303684Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review
4 !!Link opens in a new tab Citaten (Scopus) -
An Entanglement-Inspired Action Selection and Knowledge Sharing Scheme for Cooperative Multi-agent Q-Learning Algorithm used in Robot Navigation
Karami, M. H., Aghababa, H. & Keyhanipour, A. H., 31 dec. 2020, 2020 10th International Conference on Computer and Knowledge Engineering, ICCKE 2020. Institute of Electrical and Electronics Engineers, blz. 617-622 6 blz. 9303636Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic
1 !!Link opens in a new tab Citaat (Scopus)
Knipsels
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National Research Council of Canada Reports Findings in Computers (Real-time simulation of viscoelastic tissue behavior with physics-guided deep learning)
12/01/23
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