University Lecturer Heikki Huttunen, Dr.Eng.
Positions of trust:
- Pattern recognition and statistics
- Computer vision for various applications
- Signal Processing Journal Club is our
seminar on recent development in various areas of signal processing.
- Emre Cakir, Giambattista Parascandolo, Toni Heittola, Heikki
Huttunen, and Tuomas Virtanen, "Convolutional Recurrent Neural
Networks for Polyphonic Sound Event Detection," IEEE Trans. Audio,
Speech and Language Proc., 2017 (to appear)
- Lin Li, Tiziana Fanni, Timo Viitanen, Renjie Xie, Francesca Palumbo, Luigi Raffo, Heikki Huttunen, Jarmo Takala and Shuvra Bhattacharyya, "Low Power Design Methodology for Signal Processing Systems using Lightweight Dataflow Techniques", Design & Architectures for Signal & Image Processing, Rennes, France, October 12-14, 2016.
- Renjie Xie, Heikki Huttunen, Shuoxin Lin, Shuvra S. Bhattacharyya,
Jarmo Takala, "Resource-Constrained Implementation and Optimization of a
Deep Neural Network for Vehicle Classification," EUSIPCO 2016, Sept. 2016.
- Jussi Tohka, Elaheh Moradi, Heikki Huttunen, Alzheimer's Disease
Neuroimaging Initiative, "Comparison of Feature Selection Techniques in
Machine Learning for Anatomical Brain MRI in Dementia,"
Neuroinformatics, July 2016, Volume 14, Issue 3, pp 279-296.
- Heikki Huttunen, Fatemeh Shokrollahi Yancheshmeh, Ke Chen, "Car Type
Recognition with Deep Neural Networks," IEEE Intelligent Vehicles
- Andrei Cramariuc, Heikki Huttunen and Simona Lohan, "Clustering benefits
in mobile-centric WiFi positioning in multi-floor buildings," ICL-GNSS,
- Kaisa Liimatainen, Pekka Ruusuvuori, Leena Latonen and Heikki Huttunen,
"Supervised Method for Cell Counting from Bright Field Focus Stacks,"
IEEE ISBI, April 2016.
S. Sakira Hassan, Pekka Ruusuvuori, Leena Latonen and Heikki Huttunen, "Flow
Cytometry-Based Classification in Cancer Research: A View on Feature
Selection," Cancer Informatics, April 2016.
- Giambattista Parascandolo, Heikki Huttunen, Tuomas Virtanen, "Recurrent
Neural Networks for Polyphonic Sound Event Detection in Real Life
Recordings," IEEE ICASSP 2016, March 2016.
- Minnamari Vippola, Masi Valkonen, Essi Sarlin, Mari Honkanen and
Heikki Huttunen, "Insight to Nanoparticle Size Analysis---Novel and
Convenient Image Analysis Method Versus Conventional Techniques,"
Nanoscale Research Letters, March 2016.
- Tuomas Tikkanen, Pekka Ruusuvuori, Leena Latonen, and Heikki Huttunen, "Training based cell detection from bright-field microscope images,"
9th International Symposium on Image and Signal Processing and Analysis (ISPA), Sept. 2015.
- Emre Cakir, Toni Heittola, Heikki Huttunen and Tuomas Virtanen,
"Multi-Label vs. Combined Single-label Sound Event Detection with Deep
Neural Networks," EUSIPCO 2015, August 2015.
- Emre Cakir, Toni Heittola, Heikki Huttunen and Tuomas Virtanen, "Polyphonic
Sound Event Detection Using Multi Label Deep Neural Networks," in International Joint Conference on Neural
Networks, July 2015.
- Heikki Huttunen, Ke Chen, Abhishek Thakur, Artus Krohn-Grimberghe,
Oguzhan Gencoglu, Xingyang Ni, Mohammed Al-Musawi, Lei Xu, Hendrik
Jacob van Veen, "Computer Vision for Head Pose Estimation: Review of a Competition", in Scandinavian Conference on
Image Analysis (SCIA2015), June 2015 [data].
- Heikki Huttunen, Jussi Tohka, "Model
Selection for Linear Classifiers using Bayesian Error Estimation,"
Pattern Recognition, May 2015.
- Kaisa Liimatainen, Raimo Heikkilä, Olli Yli-Harja, Heikki Huttunen, Pekka Ruusuvuori, "Sparse logistic regression and polynomial modeling for detection of artificial drainage networks," in International Journal of Remote Sensing, April 2015.
- Elaheh Moradi, Antonietta Pepe, Christian Gaser, Heikki Huttunen and Jussi Tohka, "Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects," in NeuroImage, 104(1) January 2015.
- Heikki Huttunen, Oguzhan Gencoglu, Johannes Lehmusvaara, and Teemu
Vartiainen, "MEG Decoding with Hierarchical Combination
of Logistic Regression and Random Forests," Technical report of our 2nd
place submission to the DecMeg 2014
competition at Kaggle.com, Aug. 2014.
- O. Gencoglu, T. Virtanen, H. Huttunen, "Recognition of Acoustic Events Using Deep Neural Networks," in EUSIPCO 2014, Sept. 2014.
- P. Ruusuvuori, L. Paavolainen, K. Rutanen, A. Mäki, H. Huttunen, V. Marjomäki, "Quantitative analysis of dynamic association in live biological fluorescent samples," PLoS ONE, 9(4), April 2014.
- T. Manninen, H. Huttunen, P. Ruusuvuori and M. Nykter, "Leukemia
Prediction Using Sparse Logistic Regression," PLOS ONE
e72932. August 2013. [software]
- H. Huttunen, T. Manninen and J. Tohka, "Bayesian Error
and Model Selection in Sparse Logistic
Regression," IEEE MLSP,
Southampton, UK, Sept.
- Briggs et al., "The 9th annual MLSP competition: New methods for
acoustic classification of multiple simultaneous bird species in a
noisy environment," IEEE MLSP,
Southampton, UK, Sept.
- S. Hassan, M. Farhan, R. Mangayil, H. Huttunen, T. Aho, "Bioprocess data
mining using regularized regression
and random forests," BMC Systems
- H. Kikuchi, S. Kataoka, S. Muramatsu, H. Huttunen,
Similarity of Digital Images," IEEE
ICIP, Melbourne, Australia,
- N. Aghaeepour, G. Finak,
The FlowCAP Consortium,
The DREAM Consortium,
and R. Scheuermann, "Critical
assessment of automated flow cytometry data
analysis techniques," Nature Methods, February 2013.
- H. Huttunen, T. Manninen, J-P. Kauppi and J. Tohka, "Mind
Regularized Multinomial Logistic Regression," in Machine Vision
Applications, pp. 1-15, November 2012. [pdf] [software] [data]