Search Results - subject:"Image segmentation"

Combining convolution neural networks with long-short term memory layers to predict Parkinson's disease progression

Frasca, Maria; La Torre, Davide; Pravettoni, Gabriella; … - In: International transactions in operational research : a … 32 (2025) 4, pp. 2159-2188

Persistent link: https://www.econbiz.de/10015338338

Mixed-integer linear programming formulations and column generation algorithms for the Minimum Normalized Cuts problem on networks

Ponce, Diego; Puerto, Justo; Temprano, Francisco - In: European journal of operational research : EJOR 316 (2024) 2, pp. 519-538

Persistent link: https://www.econbiz.de/10014574272

Synthetic data generation using finite element method to pre-train an image segmentation model for defect detection using infrared thermography

Pareek, Kaushal Arun; May, Daniel; Meszmer, Peter; Ras, … - In: Journal of Intelligent Manufacturing 36 (2024) 3, pp. 1879-1905

representativeness of synthetic data was thoroughly investigated at various steps of the framework, and the image segmentation model was …

Persistent link: https://www.econbiz.de/10015410170

Single system for online monitoring and inspection of automated fiber placement with object segmentation by artificial neural networks

Brysch, Marco; Bahar, Mohammad; Hohensee, Hans Christoph; … - In: Journal of Intelligent Manufacturing 33 (2022) 7, pp. 2013-2025

techniques such as image segmentation with neural networks provide a new approach to this problem and have the potential to solve … identification of individual tapes, provides accurate measurements which are demonstrated by an example. We show that image … segmentation with modern approaches like SiamMask offers great potential to handle highly complex engineering tasks in a faster and …

Persistent link: https://www.econbiz.de/10015272810

Review of image segmentation techniques for layup defect detection in the Automated Fiber Placement process

Meister, Sebastian; Wermes, Mahdieu A. M.; Stüve, Jan; … - In: Journal of Intelligent Manufacturing 32 (2021) 8, pp. 2099-2119

The aerospace industry has established the Automated Fiber Placement process as a common technique for manufacturing fibre reinforced components. In this process multiple composite tows are placed simultaneously onto a tool. Currently in such processes manual testing requires often up to 50% of...

Persistent link: https://www.econbiz.de/10014501797

K-expectiles clustering

Wang, Bingling; Li, Yingxing; Härdle, Wolfgang - 2021

K-means clustering is one of the most widely-used partitioning algorithm in cluster analysis due to its simplicity and computational efficiency, but it may not provide ideal clustering results when applying to data with non-spherically shaped clusters. By considering the asymmetrically weighted...

Persistent link: https://www.econbiz.de/10012504534

K-expectiles clustering

Wang, Bingling; Li, Yingxing; Härdle, Wolfgang - 2021

Persistent link: https://www.econbiz.de/10012500154

A reproducible notebook to acquire, process and analyse satellite imagery: Exploring long-term urban changes

Chen, Meixu; Fahrner, Dominik; Arribas-Bel, Daniel; … - In: REGION 7 (2020) 2, pp. R15-R46

Satellite imagery is often used to study and monitor Earth surface changes. The open availability and extensive temporal coverage of Landsat imagery has enabled changes in temperature, wind, vegetation and ice melting speed for a period of up to 46 years. Yet, the use of satellite imagery to...

Persistent link: https://www.econbiz.de/10012591469

A reproducible notebook to acquire, process and analyse satellite imagery : exploring long-term urban changes

Chen, Meixu; Fahrner, Dominik; Arribas-Bel, Daniel; … - In: Region : the journal of ERSA 7 (2020) 2, pp. R15-R46

Persistent link: https://www.econbiz.de/10012491435

A hybrid cluster technique for improving the efficiency of colour image segmentation

Kumar, Ankit; Raja, Linesh; Dadheech, Pankaj; Bhardwaj, … - In: World review of entrepreneurship, management and … 16 (2020) 6, pp. 665-679

Persistent link: https://www.econbiz.de/10012319108