We are seeking a motivated student assistant for a project on anomaly detection for hyperspectral images.
Anomaly detection is the process of identifying data points that differ significantly from the majority of the data which has several applications, for example to detect malicious instances in manufacturing processes. Hyperspectral images capture information across a wide range of the electromagnetic spectrum (besides RGB), allowing for highly detailed and precise visual data. In this project, we want to create a setup for anomaly detection techniques to identify abnormal patterns in hyperspectral images.
As a student assistant, your responsibility will be to capture a dataset for the project. After that, initial experiments on the data should be made using basic programming knowledge and knowledge in data science and/or machine learning.
To apply, please send a short introduction of yourself, your grade transcript and a brief statement of interest to Marco Rudolph.
basic knowledge of programming (Python and/or Matlab) basic knowledge of data science and/or machine learning
Contact person: Marco Rudolph
