Academic Internship
1 semana atrás
Deep Learning models have showed good performance when solving LiDAR based 3D tasks (e.g. object detection, semantic segmentation, lane, free space estimation, etc...). But deploying a model for each task is computationally expensive, especially when similar tasks, with similar modalities/information is being considered.
This motivates the use of Multi-task networks which learn to simultaneously solve multiple related tasks.
**Your contribution to something big**:
- Create a MTL DL model from LiDAR data to solve 3D tasks;
- Compare single tasks vs multitask performance;
- Investigate relation between number of tasks vs performance and complementary vs conflicting tasks;
- Possible to use same backbone/input-representation for all tasks? Compare with of multi-input representation model.
**Qualifications**:
**What distinguishes you**:
- Attending the Master's Degree in Software Engineering / Computer Science or similar;
- Good level of English (spoken and written);
- Sense of Team Work;
- Interested in develop a Master Thesis in this area of study.
**Additional Information**:
**What we offer you**:
Challenges in an international environment | career opportunities in one of the best companies in the world | flexible hours | medical services | discounts for employees | sports and health related activities | canteen | good access to public transports | space for creativity.
**Success stories don´t just happen. They are made...**
**Job Location**:
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