World's Best Scientists 2026 revealed!
Juho Kannala

Juho Kannala

D-Index & Metrics

Computer Science

D-Index
43
Citations
12052
World Ranking
7797
National Ranking
63

Juho Kannala publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Juho Kannala sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 185 publications — 41st percentile

41% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Juho Kannala D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Juho Kannala sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

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

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Interested in expanding your qualifications beyond Computer Science? There are many majors that align well with in-demand tech careers, such as Information Technology, Data Science, or Software Engineering. Exploring related fields can diversify your skill set and open new career avenues.

For those looking to advance quickly, some easy masters degrees offer flexible coursework and minimal prerequisites—ideal for busy professionals or career changers. You can also consider doctoral programs that fit your budget and schedule, with options such as the cheapest online phd programs in tech or education-related fields.

If you’re eager to complete your studies at an accelerated pace, accelerated doctoral programs in education online provide a fast-track to advanced credentials. These pathways enable you to boost your expertise and pursue specialized roles in academia, research, or industry while studying remotely.

Best Scientists Citing Juho Kannala

Trending Scientists

Recently Published Articles