# Deep learning for tactile understanding from visual and haptic data

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/deep-learning-for-tactile-understanding-from-visual-and-haptic-data/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Yang Gao,Lisa Anne Hendricks,Katherine J. Kuchenbecker,Trevor Darrell |
| Citations | 253 |
| DOI | 10.1109/icra.2016.7487176 |
| Fields | Computer Science,Engineering,Neuroscience |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2963654998 |
| Type | conference-paper |
| Year | 2016 |

## Paper authors

- [Katherine J. Kuchenbecker](https://scholariq.org/researchers/katherine-j-kuchenbecker/)

## Paper primary topic

- [Tactile and Sensory Interactions](https://scholariq.org/topics/tactile-and-sensory-interactions/)

## Paper topics

- [Tactile and Sensory Interactions](https://scholariq.org/topics/tactile-and-sensory-interactions/)
- [Robot Manipulation and Learning](https://scholariq.org/topics/robot-manipulation-and-learning/)
- [Gaze Tracking and Assistive Technology](https://scholariq.org/topics/gaze-tracking-and-assistive-technology/)

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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.