# 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

arXiv: https://arxiv.org/abs/2107.11181 · HTML: https://mlsanity.com/paper/2107.11181/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 6 references that are in the map.
- First posted on arXiv 22 Jul 2021.

## Builds on (most cited first, 1 of 1)

- [EQSA: Earthquake Situational Analytics from Social Media](https://mlsanity.com/paper/1910.08881/) (2019)

## Abstract (arXiv)

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.