UX Heuristics and Checklist for Deep Learning powered Mobile Applications with Image Classification
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Abstract (arXiv)
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 heuristic evaluations supporting practitioners to develop image classification apps that people can understand, trust, and can engage with effectively.
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References · 7
- 2015Deep Residual Learning for Image Recognitioncited by 51,809
- 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,415
- 2017MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applicationscited by 3,827
- 2020Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthycited by 182
- 2019Human-Centered Artificial Intelligence and Machine Learningcited by 37
- 2020A Comparative Analysis of Industry Human-AI Interaction Guidelinescited by 9
- 2021Integration of Convolutional Neural Networks in Mobile Applicationscited by 6
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