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Juho Kannala

Juho Kannala

D-Index & Metrics

Computer Science

D-Index
43
Citations
12052
World Ranking
7798
National Ranking
63

Overview

Juho Kannala is affiliated with Aalto University in Finland and has a significant body of research within computer science and engineering. Their work primarily concentrates on areas such as computer vision, artificial intelligence, and aerospace engineering, with a particular focus on advanced vision and imaging techniques and robotics-based localization.

Kannala's publications showcase contributions to several subfields including computer vision and pattern recognition, artificial intelligence, aerospace engineering, electrical and electronic engineering, and geology. Their topics of study often explore:

  • Advanced Vision and Imaging
  • Robotics and Sensor-Based Localization
  • Advanced Image and Video Retrieval Techniques
  • Domain Adaptation and Few-Shot Learning
  • Reinforcement Learning in Robotics
  • 3D Surveying and Cultural Heritage
  • Multimodal Machine Learning Applications

The scientist has published extensively, with a notable presence in publication venues such as arXiv (Cornell University), the 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Lecture Notes in Computer Science, Proceedings of the AAAI Conference on Artificial Intelligence, and Computer Physics Communications.

Selected recent papers include:

  • GraphMix: Improved Training of GNNs for Semi-Supervised Learning (2021), Proceedings of the AAAI Conference on Artificial Intelligence
  • HybVIO: Pushing the Limits of Real-time Visual-inertial Odometry (2022), 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • Automated tip functionalization via machine learning in scanning probe microscopy (2021), Computer Physics Communications
  • Interpolated Adversarial Training: Achieving robust neural networks without sacrificing too much accuracy (2022), Neural Networks
  • HSCNet++: Hierarchical Scene Coordinate Classification and Regression for Visual Localization with Transformer (2024), International Journal of Computer Vision

Kannala frequently collaborates with several researchers, reflecting a network of co-authors with whom they have produced multiple publications. Key collaborators include:

  • Arno Solin
  • Esa Rahtu
  • Iaroslav Melekhov
  • Shuzhe Wang
  • Joni Pajarinen

Best Publications

  • Fine-Grained Visual Classification of Aircraft

    Subhransu Maji;Esa Rahtu;Juho Kannala;Matthew B. Blaschko

  • A generic camera model and calibration method for conventional, wide-angle, and fish-eye lenses

    J. Kannala;S.S. Brandt

  • BSIF: Binarized statistical image features

    Juho Kannala;Esa Rahtu

  • Segmenting salient objects from images and videos

    Esa Rahtu;Juho Kannala;Mikko Salo;Janne Heikkilä

  • Joint Depth and Color Camera Calibration with Distortion Correction

    C Daniel Herrera;Juho Kannala;Janne Heikkil #x E

  • Interpolation consistency training for semi-supervised learning.

    Vikas Verma;Kenji Kawaguchi;Alex Lamb;Juho Kannala

  • International Conference on Pattern Recognition

    Neslihan Bayramoglu;Juho Kannala;Janne Heikkilä

  • Deep learning for magnification independent breast cancer histopathology image classification

    Neslihan Bayramoglu;Juho Kannala;Janne Heikkila

  • Interpolation Consistency Training for Semi-supervised Learning.

    Vikas Verma;Alex Lamb;Juho Kannala;Yoshua Bengio

  • Siamese network features for image matching

    Iaroslav Melekhov;Juho Kannala;Esa Rahtu

  • Learning a category independent object detection cascade

    Esa Rahtu;Juho Kannala;Matthew Blaschko

  • Mask-RCNN and U-Net Ensembled for Nuclei Segmentation

    Aarno Oskar Vuola;Saad Ullah Akram;Juho Kannala

  • Image-Based Localization Using Hourglass Networks

    Iaroslav Melekhov;Juha Ylioinas;Juho Kannala;Esa Rahtu

  • Generating Object Segmentation Proposals Using Global and Local Search

    Pekka Rantalankila;Juho Kannala;Esa Rahtu

  • Interpolation Consistency Training for Semi-Supervised Learning

    Vikas Verma;Kenji Kawaguchi;Alex Lamb;Juho Kannala

  • Camera Relocalization by Computing Pairwise Relative Poses Using Convolutional Neural Network

    Zakaria Laskar;Iaroslav Melekhov;Surya Kalia;Juho Kannala

  • Relative Camera Pose Estimation Using Convolutional Neural Networks

    Iaroslav Melekhov;Juha Ylioinas;Juho Kannala;Esa Rahtu

  • Accurate and practical calibration of a depth and color camera pair

    C. Daniel Herrera;Juho Kannala;Janne Heikkilä

  • A generic camera calibration method for fish-eye lenses

    J. Kannala;S. Brandt

  • Hierarchical Scene Coordinate Classification and Regression for Visual Localization

    Xiaotian Li;Shuzhe Wang;Yi Zhao;Jakob Verbeek

  • Understanding Objects in Detail with Fine-Grained Attributes

    Andrea Vedaldi;Siddharth Mahendran;Stavros Tsogkas;Subhransu Maji

Frequent Co-Authors

Esa Rahtu
Esa Rahtu Tampere University
Janne Heikkilä
Janne Heikkilä University of Oulu
Simo Särkkä
Simo Särkkä Aalto University
Jiri Matas
Jiri Matas Czech Technical University in Prague
Yoshua Bengio
Yoshua Bengio University of Montreal
Adam S. Foster
Adam S. Foster Aalto University
Jakob Verbeek
Jakob Verbeek Facebook AI Research (FAIR) in Paris
Ali Borji
Ali Borji Quintic AI
Andrea Vedaldi
Andrea Vedaldi University of Oxford

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