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Potentials of Semantic Image Segmentation Using Visual Attention Networks for People with Dementia

  • Due to the increasing number of dementia patients, it is time to include the care sector in digitization as well. Digital media, for example, can be used on tablets in memory care and have considerable potential for reminiscence therapy for people with dementia. The time consuming assembly of digital media content has to be automated for the caretakers. This work analyzes the potentials of semantic image segmentation with Visual Attention Networks for reminiscence therapy sessions. These approaches enable the selection of digital images to satisfy the patients individual experience and biographically. A detailed comparison of various Visual Attention Networks evaluated by the BLEU score is shown. The most promising networks for semantic image segmentation are VGG16 and VGG19.

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Author:Liane Meßmer, Christoph ReichORCiDGND
Parent Title (English):The Upper-Rhine Artificial Intelligence Symposium, UR-AI 2021, Artificial Intelligence - Application in Life Sciences and Beyond, 27th October 2021, Kaiserslautern, Germany
Publisher:Hochschule Kaiserslautern, University of Applied Sciences
Place of publication:Kaiserslautern
Document Type:Conference Proceeding
Year of Completion:2021
Release Date:2021/12/15
Tag:Dementia; Natural language processing; Reminisence therapy; Semantic segmentation; Visual attention network
First Page:234
Last Page:243
Open-Access-Status: Open Access 
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International