University Lecturer Heikki Huttunen, Dr.Eng.

Department of Signal Processing

Tampere University of Technology

Room: TF317
E-Mail: Heikki.Huttunen@tut.fi
Phone: +358-40-849-0799

Research interests:
Positions of trust:
Recent publications:
  1. 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)
  2. 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.
  3. 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.
  4. 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.
  5. Heikki Huttunen, Fatemeh Shokrollahi Yancheshmeh, Ke Chen, "Car Type Recognition with Deep Neural Networks," IEEE Intelligent Vehicles Symposium, June 2016.
  6. Andrei Cramariuc, Heikki Huttunen and Simona Lohan, "Clustering benefits in mobile-centric WiFi positioning in multi-floor buildings," ICL-GNSS, June 2016
  7. Kaisa Liimatainen, Pekka Ruusuvuori, Leena Latonen and Heikki Huttunen, "Supervised Method for Cell Counting from Bright Field Focus Stacks," IEEE ISBI, April 2016.
  8. 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.
  9. Giambattista Parascandolo, Heikki Huttunen, Tuomas Virtanen, "Recurrent Neural Networks for Polyphonic Sound Event Detection in Real Life Recordings," IEEE ICASSP 2016, March 2016.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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].
  15. Heikki Huttunen, Jussi Tohka, "Model Selection for Linear Classifiers using Bayesian Error Estimation," Pattern Recognition, May 2015.
  16. 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.
  17. 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.
  18. 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.
  19. O. Gencoglu, T. Virtanen, H. Huttunen, "Recognition of Acoustic Events Using Deep Neural Networks," in EUSIPCO 2014, Sept. 2014.
  20. 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.
  21. T. Manninen, H. Huttunen, P. Ruusuvuori and M. Nykter, "Leukemia Prediction Using Sparse Logistic Regression," PLOS ONE 8(8): e72932. August 2013. [software]
  22. H. Huttunen, T. Manninen and J. Tohka, "Bayesian Error Estimation and Model Selection in Sparse Logistic Regression," IEEE MLSP, Southampton, UK, Sept. 2013. [software]
  23. 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. 2013.
  24. S. Hassan, M. Farhan, R. Mangayil, H. Huttunen, T. Aho, "Bioprocess data mining using regularized regression and random forests," BMC Systems Biology, 2013.
  25. H. Kikuchi, S. Kataoka, S. Muramatsu, H. Huttunen, "Color-tone Similarity of Digital Images," IEEE ICIP, Melbourne, Australia, September 2013.
  26. N. Aghaeepour, G. Finak, The FlowCAP Consortium, The DREAM Consortium, H. Hoos, T. Mosmann, R. Brinkman, R. Gottardo and R. Scheuermann, "Critical assessment of automated flow cytometry data analysis techniques," Nature Methods, February 2013.
  27. H. Huttunen, T. Manninen, J-P. Kauppi and J. Tohka, "Mind Reading with Regularized Multinomial Logistic Regression," in Machine Vision and Applications, pp. 1-15, November 2012. [pdf] [software] [data]

Competitions: Software:

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