arXiv
Open Access
2021
VisMCA: A Visual Analytics System for Misclassification Correction and Analysis. VAST Challenge 2020, Mini-Challenge 2 Award: Honorable Mention for Detailed Analysis of Patterns of Misclassification
Huyen N. Nguyen
Jake Gonzalez
Jian Guo
Ngan V. T. Nguyen
Tommy Dang
Abstrak
This paper presents VisMCA, an interactive visual analytics system that supports deepening understanding in ML results, augmenting users' capabilities in correcting misclassification, and providing an analysis of underlying patterns, in response to the VAST Challenge 2020 Mini-Challenge 2. VisMCA facilitates tracking provenance and provides a comprehensive view of object detection results, easing re-labeling, and producing reliable, corrected data for future training. Our solution implements multiple analytical views on visual analysis to offer a deep insight for underlying pattern discovery.
Penulis (5)
H
Huyen N. Nguyen
J
Jake Gonzalez
J
Jian Guo
N
Ngan V. T. Nguyen
T
Tommy Dang
Format Sitasi
Nguyen, H.N., Gonzalez, J., Guo, J., Nguyen, N.V.T., Dang, T. (2021). VisMCA: A Visual Analytics System for Misclassification Correction and Analysis. VAST Challenge 2020, Mini-Challenge 2 Award: Honorable Mention for Detailed Analysis of Patterns of Misclassification. https://arxiv.org/abs/2107.11181
Akses Cepat
Informasi Jurnal
- Tahun Terbit
- 2021
- Bahasa
- en
- Sumber Database
- arXiv
- Akses
- Open Access ✓