DeepVis: A Visual Interactive System for Exploring Performance of Deep Learning Models

Publisher:
IEEE
Publication Type:
Conference Proceeding
Citation:
2022 10th International Conference on Information and Education Technology (ICIET), 2022, 00, pp. 398-402
Issue Date:
2022-05-26
Full metadata record
Nowadays deep learning DL models have been an emerging technology because of their performances and wide acceptance in various fields However in most cases the performance analysis of DL models is not viable to understand how they predict because they are inherently considered black boxes and different models have different performance rates Ad ditionally due to a lack of highly technical expertise and domain knowledge people struggle to choose a proper model for their work Therefore to understand and improve the performance of the D L model careful selection of model layer epoch optimizer hyperparameter tuning and model visualization is essential In this paper we design an interactive visualization system named DeepVis with a wide range of performance evaluation methods that assist the non expert in adopting an appropriate model Finally we demonstrate use cases and expert opinion using a publicly available dataset to validate the usability and effectiveness of Deep Vis
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