SOM_PAK: The self-organizing map program package T Kohonen, J Hynninen, J Kangas, J Laaksonen Technical report 31, 1996, 1996 | 787 | 1996 |
Variants of self-organizing maps Kangas, Kohonen, Laaksonen, Simula, Venta International 1989 Joint Conference on Neural Networks, 517-522 vol. 2, 1989 | 531 | 1989 |
LVQ PAK: The learning vector quantization program package T Kohonen, J Hynninen, J Kangas, J Laaksonen, K Torkkola Technical report 30, 10625-10640, 1996 | 378 | 1996 |
The 2005 pascal visual object classes challenge M Everingham, A Zisserman, CKI Williams, L Van Gool, M Allan, ... Machine Learning Challenges. Evaluating Predictive Uncertainty, Visual …, 2006 | 371 | 2006 |
PicSOM–content-based image retrieval with self-organizing maps J Laaksonen, M Koskela, S Laakso, E Oja Pattern recognition letters 21 (13-14), 1199-1207, 2000 | 328 | 2000 |
Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification RM Anwer, FS Khan, J Van De Weijer, M Molinier, J Laaksonen ISPRS journal of photogrammetry and remote sensing 138, 74-85, 2018 | 277 | 2018 |
PicSOM-self-organizing image retrieval with MPEG-7 content descriptors J Laaksonen, M Koskela, E Oja IEEE Transactions on Neural Networks 13 (4), 841-853, 2002 | 273 | 2002 |
Classification with learning k-nearest neighbors J Laaksonen, E Oja Proceedings of international conference on neural networks (ICNN'96) 3, 1480 …, 1996 | 254 | 1996 |
LVQ PAK: A program package for the correct application of Learning Vector Quantization algorithms T Kohonen, J Kangas, J Laaksonen, K Torkkola Proc. IJCNN 92, 725-730, 1992 | 230 | 1992 |
Neural and statistical classifiers-taxonomy and two case studies L Holmstrom, P Koistinen, J Laaksonen, E Oja IEEE Transactions on Neural Networks 8 (1), 5-17, 1997 | 193 | 1997 |
Statistical shape features for content-based image retrieval S Brandt, J Laaksonen, E Oja Journal of Mathematical Imaging and Vision 17, 187-198, 2002 | 186 | 2002 |
Self-organising maps as a relevance feedback technique in content-based image retrieval J Laaksonen, M Koskela, S Laakso, E Oja Pattern Analysis & Applications 4, 140-152, 2001 | 149 | 2001 |
Deep contextual attention for human-object interaction detection T Wang, RM Anwer, MH Khan, FS Khan, Y Pang, L Shao, J Laaksonen Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 144 | 2019 |
Using diversity of errors for selecting members of a committee classifier M Aksela, J Laaksonen Pattern Recognition 39 (4), 608-623, 2006 | 134 | 2006 |
An augmented reality interface to contextual information A Ajanki, M Billinghurst, H Gamper, T Järvenpää, M Kandemir, S Kaski, ... Virtual reality 15, 161-173, 2011 | 129 | 2011 |
Picsom: Self-organizing maps for content-based image retrieval J Laaksonen, M Koskela, E Oja IJCNN'99. International Joint Conference on Neural Networks. Proceedings …, 1999 | 127 | 1999 |
Frame-and segment-level features and candidate pool evaluation for video caption generation R Shetty, J Laaksonen Proceedings of the 24th ACM international conference on Multimedia, 1073-1076, 2016 | 104 | 2016 |
Paying attention to descriptions generated by image captioning models HR Tavakoli, R Shetty, A Borji, J Laaksonen Proceedings of the IEEE international conference on computer vision, 2487-2496, 2017 | 92 | 2017 |
The MeMAD submission to the WMT18 multimodal translation task SA Grönroos, B Huet, M Kurimo, J Laaksonen, B Merialdo, P Pham, ... arXiv preprint arXiv:1808.10802, 2018 | 82 | 2018 |
Exploiting inter-image similarity and ensemble of extreme learners for fixation prediction using deep features HR Tavakoli, A Borji, J Laaksonen, E Rahtu Neurocomputing 244, 10-18, 2017 | 81 | 2017 |