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Jorma Laaksonen

Jorma Laaksonen

D-Index & Metrics

Computer Science

D-Index
41
Citations
8894
World Ranking
8706
National Ranking
71

Overview

Jorma Laaksonen is a researcher affiliated with Aalto University in Finland, specializing in the field of computer science. Their academic work focuses extensively on computer vision and pattern recognition, encompassing a total of 65 publications in this subfield. Other notable areas of study include artificial intelligence, media technology, signal processing, and general health professions.

The primary research themes in Laaksonen's work cover a broad range of topics related to image and video analysis and multimodal learning. The main topics addressed in their publications are as follows:

  • Multimodal Machine Learning Applications
  • Advanced Image and Video Retrieval Techniques
  • Domain Adaptation and Few-Shot Learning
  • Human Pose and Action Recognition
  • Advanced Image Processing Techniques
  • Biometric Identification and Security
  • Face recognition and analysis

Laaksonen has contributed substantially to various publication venues. They have 21 papers published in the arXiv repository, making it the most frequent platform for their research dissemination. Other outlets include the International Journal of Computer Vision and Pattern Recognition Letters, with two publications each, as well as Remote Sensing and Zenodo (CERN European Organization for Nuclear Research).

Among the recent papers associated with Laaksonen's work are:

  • "Multi-Hazard and Spatial Transferability of a CNN for Automated Building Damage Assessment," 2020, Remote Sensing
  • "XrayGPT: Chest Radiographs Summarization using Medical Vision-Language Models," 2023, arXiv (Cornell University)
  • "Bilateral Reference for High-Resolution Dichotomous Image Segmentation," 2024, CAAI Artificial Intelligence Research
  • "Compact Deep Color Features for Remote Sensing Scene Classification," 2021, Neural Processing Letters
  • "Tackling the Unannotated: Scene Graph Generation with Bias-Reduced Models," 2020, arXiv (Cornell University)

Laaksonen frequently collaborates with a number of coauthors across their research projects. The coauthors with whom they have most often worked include:

  • Rao Muhammad Anwer
  • Fahad Shahbaz Khan
  • Usman Muhammad
  • Hisham Cholakkal
  • Tzu-Jui Julius Wang

Best Publications

  • SOM_PAK: The Self-Organizing Map Program Package

    T. Kohonen;J. Hynninen;J. Kangas;J. Laaksonen

  • Variants of self-organizing maps

    J.A. Kangas;T.K. Kohonen;J.T. Laaksonen

  • The 2005 PASCAL visual object classes challenge

    Mark Everingham;Andrew Zisserman;Christopher K. I. Williams;Luc Van Gool

  • Variants of self-organizing maps.

    Kangas J;Kohonen T;Laaksonen J;Simula O

  • LVQ_PAK: The Learning Vector Quantization Program Package

    T. Kohonen;J. Hynninen;J. Kangas;J. Laaksonen

  • PicSOM—content-based image retrieval with self-organizing maps

    Jorma Laaksonen;Markus Koskela;Sami Laakso;Erkki Oja

  • Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification

    Rao Muhammad Anwer;Fahad Shahbaz Khan;Joost van de Weijer;Matthieu Molinier

  • PicSOM-self-organizing image retrieval with MPEG-7 content descriptors

    J. Laaksonen;M. Koskela;E. Oja

  • Classification with learning k-nearest neighbors

    J. Laaksonen;E. Oja

  • LVQPAK: A software package for the correct application of Learning Vector Quantization algorithms

    T. Kohonen;J. Kangas;J. Laaksonen;K. Torkkola

  • Neural and statistical classifiers-taxonomy and two case studies

    L. Holmstrom;P. Koistinen;J. Laaksonen;E. Oja

  • Statistical Shape Features for Content-Based Image Retrieval

    Sami Brandt;Jorma Laaksonen;Erkki Oja

  • Statistical shape features in content-based image retrieval

    S. Brandt;J. Laaksonen;E. Oja

  • Self-Organising Maps as a Relevance Feedback Technique in Content-Based Image Retrieval

    Jorma Laaksonen;Markus Koskela;Sami Laakso;Erkki Oja

  • An Augmented Reality Interface to Contextual Information

    Antti Ajanki;Mark Billinghurst;Hannes Gamper;Toni Jarvenpaa

  • Using diversity of errors for selecting members of a committee classifier

    Matti Aksela;Jorma Laaksonen

  • Deep Contextual Attention for Human-Object Interaction Detection

    Tiancai Wang;Rao Muhammad Anwer;Muhammad Haris Khan;Fahad Shahbaz Khan

  • PicSOM: self-organizing maps for content-based image retrieval

    J. Laaksonen;M. Koskela;E. Oja

  • Proceedings of the International Conference on Speech Prosody

    Tommi Jantunen;Johanna Mesch;Anna Puupponen;Jorma Laaksonen

  • Frame- and Segment-Level Features and Candidate Pool Evaluation for Video Caption Generation

    Rakshith Shetty;Jorma Laaksonen

Frequent Co-Authors

Erkki Oja
Erkki Oja Aalto University
Fahad Shahbaz Khan
Fahad Shahbaz Khan Mohamed bin Zayed University of Artificial Intelligence
Mikko Kurimo
Mikko Kurimo Aalto University
Samuel Kaski
Samuel Kaski Aalto University
Joost van de Weijer
Joost van de Weijer Autonomous University of Barcelona
Ali Borji
Ali Borji Quintic AI
Teuvo Kohonen
Teuvo Kohonen Aalto University
Michael Felsberg
Michael Felsberg Linköping University
John Shawe-Taylor
John Shawe-Taylor University College London
Peter Auer
Peter Auer University of Leoben

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