Dipl.-Ing. André Kelm


(040) 6541-3738
(040) 6541-2834
Visitor Address
Building H3
Holstenhofweg 85
22043 Hamburg
Postal Address
Faculty of Electrical Engineering
Signal Processing and Communications
P.O. Box 70 08 22
22008 Hamburg


Aim is the segmentation and classification of images in the maritime environment. For this purpose, mainly convolutional neural nets are used. Novel methods are investigated and, if necessary, adapted or developed. Classical image processing algorithms are used to support segmentation.


Segmentation CNN


To understand the scene of the image, new interesting classes like water, sky, … and many more are learned.

Ship-Scene-Segmentation CNN

To support the classification task, a contour extraction method with deep learning was implemented.

Contour Extraction CNN

The RefineContourNet uses an established segmentation network and reaches State-of-the-Art in edge-detection on the BSDS500 Benchmark: BSDS500 SoA

Test-Code on  https://github.com/AndreKelm/RefineContourNet


Supervised project work

Vijesh Sao Rao – Training State-of-the-Art CNNs for Segmentation and Contour Detection on Ship Images, Student Project

Christina Sander – SSD Analysis and Development of Adaption Proposal for a CNN Ship Detector, Student Project

Supradeep Chikaballapur Manjunath – Contour Detection using SRCNN,  Student Project

Karthik Kadur Manjunath – Analysing Hypercolumn Features for Object Contour detection and Semantic Segmentation,  Student Project

Supervised Master Theses

Vijesh Sao Rao – Generating synthetic NIR images from RGB images using GANs, Master Thesis

Rocío Aldana Figueroa – CNN for Detailed Ship Image Segmentation using Contour and Segmentation Feature Maps, Master Thesis

Sous-Lieutenant Jean Fissot – Using Phase-Stretch-Transform Algorithm as an Image-Feature-Extractor, Master Thesis


A. Kelm, V. Rao, U. Zölzer: Object Contour and Edge Detection with RefineContourNet – Computer Analysis of Images and Patterns, 18th International Conference, CAIP 2019, Salerno, Italy, September 3–5, 2019, Proceedings, Part I

P. Bhattacharya, G. Simkus, C. de Obaldía, A. Kelm, U. Zölzer: Convolutional Neural Networks for Digital Signal Processing, LSA2017 – Lübeck Summer Academy on Medical Technology, July 2017, Lübeck, Germany.



Letzte Änderung: 30. March 2020