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Fysihka ja teknologiija instituhtta changkyu.choi@uit.no You can find me here

Changkyu Choi

  • Hyeongji Kim, Changkyu Choi, Michael Christian Kampffmeyer, Terje Berge, Pekka Parviainen, Ketil Malde :
    ProxyDR: Deep Hyperspherical Metric Learning with Distance Ratio-Based Formulation
    Lecture Notes in Computer Science (LNCS) 2024
  • Changkyu Choi, Shujian Yu, Michael Christian Kampffmeyer, Arnt-Børre Salberg, Nils Olav Handegard, Robert Jenssen :
    DIB-X: Formulating Explainability Principles for a Self-Explainable Model Through Information Theoretic Learning
    Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing 2024 DOI
  • Changkyu Choi, Michael Kampffmeyer, Nils Olav Handegard, Arnt-Børre Salberg, Robert Jenssen :
    Deep Semisupervised Semantic Segmentation in Multifrequency Echosounder Data
    IEEE Journal of Oceanic Engineering 2023 ARKIV / DOI
  • Changkyu Choi, Michael Kampffmeyer, Nils Olav Handegard, Arnt Børre Salberg, Olav Brautaset, Line Eikvil et al.:
    Semi-supervised target classification in multi-frequency echosounder data
    ICES Journal of Marine Science 12. Aug 2021 ARKIV / FULLTEKST / DOI
  • Changkyu Choi, Filippo Maria Bianchi, Michael Kampffmeyer, Robert Jenssen :
    Short-Term Load Forecasting with Missing Data using Dilated Recurrent Attention Networks
    Proceedings of the Northern Lights Deep Learning Workshop 2020 ARKIV / DOI
  • Adín Ramírez Rivera, Sarina Thomas, Changkyu Choi :
    Unsupervised Learning of visual feature hierarchy by contrasting hierarchical topic assignments
    2024
  • Changkyu Choi :
    Introduction to generative AI
    2023
  • Changkyu Choi :
    DIB-X: Formulating Explainability Principles for a Self-explainable Model through Information Theoretic Learning
    2023
  • Changkyu Choi :
    Deep learning landscape 2: Image tasks and CNNs
    2023
  • Changkyu Choi :
    Deep learning landscape 1: Neural networks basic
    2023
  • Changkyu Choi :
    Recent Deep Learning Models and their Applicability in the Marine Domain Now and in the Near Future
    2023
  • Changkyu Choi, Michael Christian Kampffmeyer, Nils Olav Handegard, Arnt-Børre Salberg, Robert Jenssen :
    Deep Semi-supervised Semantic Segmentation in Multi-frequency Echosounder Data
    2023
  • Changkyu Choi :
    Deep learning landscape 4: Transformers and their applicability in the marine domain now and in the near future
    2023
  • Changkyu Choi :
    Deep learning landscape 3: Explainable deep learning
    2023
  • Changkyu Choi :
    Recent Deep Learning Models and their Applicability in the Marine Domain Now and in the Near Future
    2023
  • Changkyu Choi, Shujian Yu, Michael Kampffmeyer, Arnt-Børre Salberg, Nils Olav Handegard, Suaiba Amina Salahuddin et al.:
    Explaining Marine Acoustic Target Classification in Multi-channel Echosounder Data using Self-attention Mask, Information-Bottleneck, and Mask Prior
    2022
  • Nils Olav Handegard, Olav Brautaset, Changkyu Choi, Tomasz Furmanek, Arne Johan Hestnes, Espen Johnsen et al.:
    Developing and deploying machine learning methods for acoustic data
    2022 PROSJEKT
  • Changkyu Choi :
    Segmenting Multi-frequency Marine Acoustic Data in a Semi-supervised Fashion
    2022
  • Changkyu Choi :
    Information Bottleneck-based Interpretability Method in Marine Acoustic Data
    2022
  • Changkyu Choi :
    Deep Semi-supervised Target Classification in Multi-frequency Echosounder Data
    2021
  • Changkyu Choi :
    Semi-supervised Semantic Segmentation in Multi-frequency Echosounder Data
    2021 FULLTEKST
  • Changkyu Choi :
    Marine Vision: When Visual Intelligence meets Marine Science
    2021 FULLTEKST
  • Changkyu Choi, Michael Kampffmeyer, Nils Olav Handegard, Arnt Børre Salberg, Line Eikvil, Robert Jenssen :
    Semi-supervised Semantic Segmentation in Multi-frequency Echosounder Data
    2021
  • Nils Olav Handegard, Lars Nonboe Andersen, Olav Brautaset, Changkyu Choi, Inge Kristian Eliassen, Yngve Heggelund et al.:
    Fisheries acoustics and Acoustic Target Classification - Report from the COGMAR/CRIMAC workshop on machine learning methods in fisheries acoustics
    2021 FULLTEKST / ARKIV
  • Nils Olav Handegard, Changkyu Choi :
    Arbeidet hans sparer forskerne for store ressurser, og åpner for et selvstyrt fiskeri
    26. Aug 2021 FULLTEKST
  • Changkyu Choi :
    Semisupervised target classification in multifrequency echosounder data
    2020
  • Changkyu Choi, Filippo Maria Bianchi, Michael Kampffmeyer, Robert Jenssen :
    Short-Term Load Forecasting with Missing Data using Dilated Recurrent Attention Networks
    2020 ARKIV / FULLTEKST
  • Changkyu Choi, Michael Kampffmeyer, Robert Jenssen :
    A Robustness Analysis of Personalized Propagation of Neural Prediction
    2020 ARKIV

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    Machine Learning   Norsk innhold