UX Heuristics and Checklist for Deep Learning powered Mobile Applications with Image Classification
Christiane Gresse von Wangenheim, Gustavo Dirschnabel

TL;DR
This paper proposes a set of usability heuristics and a checklist for designing user-friendly deep learning-powered mobile image classification apps, supported by an online course and evaluation tool.
Contribution
It introduces a tailored set of AIX heuristics for mobile image classification apps, including a checklist, online training, and a web-based evaluation tool.
Findings
Developed initial AIX heuristics for deep learning mobile apps
Created an online course and web tool for heuristic evaluation
Guided design and evaluation of user-friendly image classification apps
Abstract
Advances in mobile applications providing image classification enabled by Deep Learning require innovative User Experience solutions in order to assure their adequate use by users. To aid the design process, usability heuristics are typically customized for a specific kind of application. Therefore, based on a literature review and analyzing existing mobile applications with image classification, we propose an initial set of AIX heuristics for Deep Learning powered mobile applications with image classification decomposed into a checklist. In order to facilitate the usage of the checklist we also developed an online course presenting the concepts and heuristics as well as a web-based tool in order to support an evaluation using these heuristics. These results of this research can be used to guide the design of the interfaces of such applications as well as support the conduction of…
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Taxonomy
TopicsIoT and Edge/Fog Computing · Green IT and Sustainability · AI in Service Interactions
