Welcome to my page!

My name is Arne Bechensteen, and I am currently an R&D engineer at Kongsberg Maritime in Horten, Norway.

Bio

I have an engineering degree from INSA Toulouse in applied mathematics, with a specialization in numerical models and optimization.

I started my Ph.D. in October 2017 with Laure Blanc-Féraud as my thesis director and Gilles Aubert as my co-supervisor. My Ph.D. was centered around sparse optimization and super-resolution microscopy, and was done in the Morpheme team in Sophia Antipolis, France. The thesis was awarded best thesis by EDSTIC in Automatic, Signal and Image processing. You can find my thesis here.

Here is my resume.

Publications

• Arne Bechensteen and Laure Blanc-Féraud and Gilles Aubert. New l2-l0 algorithm for single-molecule localization microscopy. Biomedical Optics Express 11(2) 2020 DOI, Codes

• Arne Bechensteen and Laure Blanc-Féraud and Gilles Aubert. Exact biconvex reformulation for the l2-l0 minimization problem. GRETSI 2019 pdf

• Arne Bechensteen and Laure Blanc-Féraud and Gilles Aubert. New Methods for l2-l0 Minimization and their Applications to 2D Single-Molecule Localization Microscopy. 2019 IEEE 16th International Symposium on Biomedical Imaging DOI

• Arne Bechensteen and Laure Blanc-Féraud and Gilles Aubert. A continuous relaxation of the constrained l2 − l0 problem. DOI, pdf, Codes

Internal publication

• Tallak H. Risdal, Arne H. Bechensteen. High-speed video of APEX test firings: Results of data reduction to determine fragment velocities and direction. Norwegian Defence Research Establishment (FFI) report no: 14/01621. Confidential publication.

Teaching

All my teaching has been done at Polytech Nice Sophia. I have taught mainly for students in L1 or M2, which is the first year of engineering school, and the last year.

2019-2020

• M2: Machine Learning Avancé 8h (Advanced Machine learning)
  • Including: Support Vector Machine, Image enhancing, Dictionary learning and image compression
• M2: Applied AI 2h
  • Including: Treating biological data.
• L1: Outils pour la physique, 42h, (Tools for physics)
  • This class gives the basics notations and tools from mathematics to use in physics.
• L1: Programmation impérative, 13h30 (Imperative programming)
  • This class consists of giving a view into programming, using Python.

2018-2019

• L1: Outils pour la physique, 42h, (Tools for physics)
  • This class gives the basics notations and tools from mathematics to use in physics.
• L1: Programmation impérative, 12h (Imperative programming)
  • This class consists of giving a view into programming, using Python.
• M2: Traitement Numérique des Images, 10h (Image processing)
  • Including: Image segmentation, image processing using variational approaches, partial differential equations and images, and Mathematical morphology.

2017-2018

• L1: Outils pour la physique, 36h, (Tools for physics)
  • This class gives the basics notations and tools from mathematics to use in physics.
• L1: Programmation impérative, 29.5h (Imperative programming)
  • This class consists of giving a view into programming, using Python.