Professori Lasse Lensu

E-mail: lasse.lensu@lut.fi
Mobile phone: +358 407591720
ORCID ID: 0000-0002-7691-121X (Go to ORCID profile)
CV:
Uploaded on: 27/11/2020

Current Organisation
Computational and Process Engineering (Superior organisation: LUT School of Engineering Science)

Biography
Lasse Lensu is a professor of machine vision and data analysis at Lappeenranta-Lahti University of Technology LUT, Finland. He received his D.Sc. (Tech.) degree in computer science and engineering in 2002 from the Department of Information Technology of LUT. His research interests include machine/computer vision, pattern recognition with machine learning and data analysis. Prof. Lensu is the head of the Department of Computational and Process Engineering at LUT, and he has contributed to the technology transfer to three spin-off companies from the university.

Research Interest
Computer/machine vision, pattern recognition, machine learning, data analysis, digital imaging, image processing, medical image analysis.

Teaching Experience
Teaching experience at LUT at the bachelor, master and post-graduate level from the year 1996. The number of courses: 20; the number of course implementations: 48. Administrative responsibilities in education include the following: Head of the Degree Programme, Chairman of Curriculum working group.

Projects as Principal Investigator
Re-engineering retinal imaging with photonics and computational science (01/01/2015 - 31/08/2015)
Funder: Academy of Finland



Projects as Project Manager
Re-engineering retinal imaging with photonics and computational science (01/01/2015 - 31/08/2015)
Funder: Academy of Finland



Projects as Co-Investigator
Leap of Digitalisation for Sawmill Industry (01/01/2018 - 31/12/2019)
Funder: Tekes



Publications
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Assessing the performance of deep learning models for multivariate probabilistic energy forecasting (2021)
A1 Journal article (refereed), original research
Mashlakov Aleksei, Kuronen Toni, Lensu Lasse, et al.
Applied Energy
Active learning of the ground truth for retinal image segmentation (2020)
A1 Journal article (refereed), original research
Nedoshivina Liubov, Lensu Lasse
Journal of Optical Technology
Evaluation of Unconditioned Deep Generative Synthesis of Retinal Images (2020)
A4 Conference proceedings
Kaplan Sinan, Lensu Lasse, Laaksonen Lauri, et al.
Lecture Notes in Computer Science
Advanced Concepts for Intelligent Vision Systems
Modelling internal knot distribution using external log features (2020)
A1 Journal article (refereed), original research
Zolotarev Fedor, Eerola Tuomas, Lensu Lasse, et al.
Computers and Electronics in Agriculture
On the Uncertainty of Retinal Artery-Vein Classification with Dense Fully-Convolutional Neural Networks (2020)
A4 Conference proceedings
Garifullin Azat, Lensu Lasse, Uusitalo Hannu
Lecture Notes in Computer Science
Advanced Concepts for Intelligent Vision Systems
Towards operational phytoplankton recognition with automated high-throughput imaging and compact convolutional neural networks (2020)
B1 Unrefereed journal article
Eerola Tuomas, Kraft Kaisa, Grönberg Osku, et al.
Weight Averaging Impact on the Uncertainty of Retinal Artery-Venous Segmentation (2020)
A4 Conference proceedings
Lindén Markus, Garifullin Azat, Lensu Lasse
Lecture Notes in Computer Science
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis
Yet Another Study on Active Learning and Human Pose Estimation (2020)
A4 Conference proceedings
Kaplan Sinan, Lensu Lasse
2nd ICML 2020 Workshop on Human in the Loop Learning (HILL)
3D Hand Movement Measurement Framework for Studying Human-Computer Interaction (2019)
A4 Conference proceedings
Kuronen Toni, Eerola Tuomas, Lensu Lasse, et al.
Lecture Notes in Networks and Systems
Cyber-Physical Systems and Control
Color-Sensitive Biosensors for Imaging Applications (2019)
A3 Book section, chapters in research books
Lensu Lasse, Frydrych Michael, Parkkinen Sinikka, et al.
Smart Biosensor Technology



Keywords
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Computer vision
Data analysis
Digital imaging
Image processing
Machine learning

Last updated on 2020-27-11 at 17:01