# Learning rewards for robotic ultrasound scanning using probabilistic\n temporal ranking

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/learning-rewards-for-robotic-ultrasound-scanning-using-probabilistic-n-temporal/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Michael Burke,Katie Lu,Daniel Angelov,Artūras Straižys,Craig Innes,Kartic Subr,Subramanian Ramamoorthy |
| Citations | 1 |
| DOI | 10.48550/arxiv.2002.01240 |
| Fields | Biochemistry, Genetics and Molecular Biology,Computer Science,Engineering |
| Open Access | true |
| OA Status | green |
| OA URL | https://arxiv.org/pdf/2002.01240 |
| OpenAlex ID | https://openalex.org/W4382132587 |
| Type | preprint |
| Year | 2020 |

## Paper authors

- [Artūras Straižys](https://scholariq.org/researchers/arturas-straizys/)

## Paper journal

- [arXiv (Cornell University)](https://scholariq.org/journals/arxiv-cornell-university/)

## Paper primary topic

- [Robotics and Sensor-Based Localization](https://scholariq.org/topics/robotics-and-sensor-based-localization/)

## Paper topics

- [Robotics and Sensor-Based Localization](https://scholariq.org/topics/robotics-and-sensor-based-localization/)
- [Domain Adaptation and Few-Shot Learning](https://scholariq.org/topics/domain-adaptation-and-few-shot-learning/)
- [Single-cell and spatial transcriptomics](https://scholariq.org/topics/single-cell-and-spatial-transcriptomics/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.