Areas Christoph Bültemann is Knowledgeable in:
Detecting states via optical, noise or other sensor data by analyzing the data
Development of devices or machinery or software.
Techniques Christoph Bültemann Uses:
LEAD user method
Christoph Bültemann's Problem Solving Experience:
Created various automotive HMI prototypes in the area of ADAS and autonomous driving using various I/O modalities
Developed high speed error reconstruction algorithms based on meta-programming for the semiconductor testing industry. Achieved speed-up by several magnitudes.
Developed a machine learning system based on genetic programming with flexible command set for pattern recognition, data processing/analysis, image recognition, voice recognition
Developed a Fingerprint recognition system from scratch: Image recognition, Pattern matching, Template generation, Algorithms, partially based on genetic programming
Developed a numberplate recognition system for any footage, used to anonymize license plates
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