BiMAE – A Bimodal Masked Autoencoder Architecture for Single-Label Hyperspectral Image Classification

• M. Kholiavchenko, J. Kline, M. Kukushkin, O. Brookes, S. Stevens, I. Duporge, A. Sheets, R. R Babu, N. Banerji, E. Campolongo, M. Thompson, N. Van Tiel, J. Miliko, E. Bessa, M. Mirmehdi, T. Schmid, T. Berger-Wolf, D. I Rubenstein, T. Burghardt, C. V Stewart
  Deep dive into KABR: a dataset for understanding ungulate behavior from in-situ drone video | LINK
  

  Multimedia Tools and Applications, Springer US (2024)

• M. Kukushkin, M. Bogdan, T. Schmid
  BiCAE – A Bimodal Convolutional Autoencoder for Seed Purity Testing | LINK
  

  Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML & PKDD), pp. 447-462, Springer, 2024

• M. Kukushkin, M. Bogdan, T. Schmid
  BiMAE – A Bimodal Masked Autoencoder Architecture for Single-Label Hyperspectral Image Classification | LINK
  

  Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024, pp. 2987-2996

• M. Kukushkin, M. Bogdan, T. Schmid
  On optimizing morphological neural networks for hyperspectral image classification | LINK
  

  International Conference on Machine Vision (ICMV-2023), 15-18. Nov, Yerevan, Armenia, 2023

• F. Erichsmeier, M. Kukushkin, J. Fiedler, M. Enders, S. Goertz, M. Bogdan, T. Schmid, R. Kaschuba
  Automating the purity analysis of oilseed rape through usage of hyperspectral imaging | LINK
  

  Proc. SPIE 12879, Photonic Technologies in Plant and Agricultural Science, 128790E, 2024