Student mathematics, computer science, optical engineering or similar (f/m/x) - Tree Detection and Reconstruction using Multi-Sensor Fusion

Location

Sankt Augustin | Germany

Job description

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Course paper / final thesis

Tree Detection and Reconstruction using Multi-Sensor Fusion

Institute for the Protection of Terrestrial Infrastructures (Credits: DLR)

Starting date

immediately

Duration of contract

limited to 6 months

Remuneration

up to German TVöD 5

Type of employment

Part-time

Digital twins and virtual replicas of physical entities, processes, or systems have a broad range of applications across various industries and domains. Their unique capacity to connect the physical and digital worlds empowers organizations to simulate, monitor, and optimize real-world assets and operations, making them a promising technological advancement. However, generating functional replicas of indoor or outdoor environments typically involves a substantial amount of manual effort, especially when striving for a high level of detail. In the context of outdoor models, the reconstruction and localization of lifelike vegetation, such as trees, can be particularly time-consuming. To streamline the generation process, leveraging deep learning techniques and effectively harnessing diverse sensor data, can offer substantial benefits. 

Therefore, the objective of this work is the detection and reconstruction of trees employing data from multiple optical sensing technologies. This includes 

• the detection and/or segmentation of trees based on different data types and sources (e.g., RGB, Lidar) using state-of-the-art deep learning techniques 
• fusing detection and/or segmentation outcomes to enhance predictive reliability 
• processing the gathered information to reconstruct the trees for deployment in a 3D world

• currently enrolled as a Master student in computer science, mathematics, optical engineering or similar major
• experience in deep learning, especially in terms of object detection or segmentation
• basic Python skills (ideally with respect to deep learning applications, e.g., PyTorch or Tensorflow)
• experience in processing point clouds is beneficial, but not required
• knowledge of the German language is preferable, but not required

Look forward to a fulfilling job with an employer who appreciates your commitment and supports your personal and professional development. Our unique infrastructure offers you a working environment in which you have unparalleled scope to develop your creative ideas and accomplish your professional objectives. Our human resources policy places great value on a healthy family and work-life-balance as well as equal opportunities for persons of all genders (f/m/x). Individuals with disabilities will be given preferential consideration in the event their qualifications are equivalent to those of other candidates.

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