# Robustness and Visual Explanation for Black Box Image, Video, and ECG Signal Classification with Reinforcement Learning

arXiv: https://arxiv.org/abs/2403.18985 · HTML: https://mlsanity.com/paper/2403.18985/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Placed in RL for clinical treatment and surgery, one of 15 directions in Deep reinforcement learning methods.
- Builds on 8 of its 21 references that are in the map.
- First posted on arXiv 27 Mar 2024.

## Placed in

- Deep reinforcement learning methods / [RL for clinical treatment and surgery](https://mlsanity.com/deeprl/rl-for-clinical-treatment-and-surgery/)

## Builds on (most cited first, 8 of 8)

- [Proximal Policy Optimization Algorithms](https://mlsanity.com/paper/1707.06347/) (2017)
- [Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization](https://mlsanity.com/paper/1610.02391/) (2016)
- [Square Attack: a query-efficient black-box adversarial attack via random search](https://mlsanity.com/paper/1912.00049/) (2019)
- [Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?](https://mlsanity.com/paper/2011.09533/) (2020)
- [A Survey of Black-Box Adversarial Attacks on Computer Vision Models](https://mlsanity.com/paper/1912.01667/) (2019)
- [RTDK-BO: High Dimensional Bayesian Optimization with Reinforced Transformer Deep kernels](https://mlsanity.com/paper/2310.03912/) (2023)
- [Skip Training for Multi-Agent Reinforcement Learning Controller for Industrial Wave Energy Converters](https://mlsanity.com/paper/2209.05656/) (2022)
- [Benchmark Generation Framework with Customizable Distortions for Image Classifier Robustness](https://mlsanity.com/paper/2310.18626/) (2023)

## Built on by (most cited first, 4 of 4)

- [Reinforcement Learning Platform for Adversarial Black-box Attacks with Custom Distortion Filters](https://mlsanity.com/paper/2501.14122/) (2025)
- [ConformalShift: Targeted Event Reordering Against Adaptive ECG Monitoring](https://mlsanity.com/paper/2608.03628/) (2026)
- [Coordinated Robustness Evaluation Framework for Vision-Language Models](https://mlsanity.com/paper/2506.05429/) (2025)
- [Robustness Evaluation for Video Models with Reinforcement Learning](https://mlsanity.com/paper/2506.05431/) (2025)

## Abstract (arXiv)

We present a generic Reinforcement Learning (RL) framework optimized for crafting adversarial attacks on different model types spanning from ECG signal analysis (1D), image classification (2D), and video classification (3D). The framework focuses on identifying sensitive regions and inducing misclassifications with minimal distortions and various distortion types. The novel RL method outperforms state-of-the-art methods for all three applications, proving its efficiency. Our RL approach produces superior localization masks, enhancing interpretability for image classification and ECG analysis models. For applications such as ECG analysis, our platform highlights critical ECG segments for clinicians while ensuring resilience against prevalent distortions. This comprehensive tool aims to bolster both resilience with adversarial training and transparency across varied applications and data types.