mlsanityData to 7 Oct 2026

VISHIEN-MAAT: Scrollytelling visualization design for explaining Siamese Neural Network concept to non-technical users

arXiv 2304.03288 ↗First posted 4 Apr 2023cs.HC cs.LGcited by 1

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Abstract (arXiv)

The past decade has witnessed rapid progress in AI research since the breakthrough in deep learning. AI technology has been applied in almost every field; therefore, technical and non-technical end-users must understand these technologies to exploit them. However existing materials are designed for experts, but non-technical users need appealing materials that deliver complex ideas in easy-to-follow steps. One notable tool that fits such a profile is scrollytelling, an approach to storytelling that provides readers with a natural and rich experience at the reader's pace, along with in-depth interactive explanations of complex concepts. Hence, this work proposes a novel visualization design for creating a scrollytelling that can effectively explain an AI concept to non-technical users. As a demonstration of our design, we created a scrollytelling to explain the Siamese Neural Network for the visual similarity matching problem. Our approach helps create a visualization valuable for a short-timeline situation like a sales pitch. The results show that the visualization based on our novel design helps improve non-technical users' perception and machine learning concept knowledge acquisition compared to traditional materials like online articles.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 7 of its 29 references that are in the map. First posted on arXiv 4 Apr 2023.

Builds on

7 of 29 references.

References · 7

  1. 2015FaceNet: A Unified Embedding for Face Recognition and Clusteringcited by 2,833
  2. 2016The Mythos of Model Interpretabilitycited by 716
  3. 2015Metric Learning with Adaptive Density Discriminationcited by 40
  4. 2015Learning Visual Clothing Style with Heterogeneous Dyadic Co-occurrencescited by 33
  5. 2020Fisher Discriminant Triplet and Contrastive Losses for Training Siamese Networkscited by 15
  6. 2019MILDNet: A Lightweight Single Scaled Deep Ranking Architecturecited by 2
  7. 2020Bubble Storytelling with Automated Animation: A Brexit Hashtag Activism Case Studycited by 2

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