Changkyu Choi introducing his Thesis.
Image:
Harald Lykke Joakimsen

Changkyu Choi introducing his Thesis.

High Quality PhD defense in the Visual Intelligence research centre

Changkyu Choi defended his PhD thesis “Advancing Deep Learning for Marine Environment Monitoring” on June 9th 2023 at UiT The Arctic University of Norway.

High Quality PhD defense in the Visual Intelligence research centre

The key objectives of Changkyu Choi thesis is advancing both deep learning and marine environment monitoring, this by addressing the challenges linked to limited annotated data. Choi has develop a new explainable deep learning method that generates explanations tailored to the needs and preferences of the  users and evaluated these in the  context of marine environment monitoring.

Changkyu Choi (center) with comitee and advisors. (Photo Harald Lykke Joakimsen)

Evaluation Committee

  • Associate Prof. Vedrana Dahl, Department of Applied Mathematics and Computer Science, Technical University of Denmark (1. Opponent)
  • Prof. Morten Goodwin, Department of Information and communication technology, University of Agder (2. Opponent)
  • Associate Prof. Benjamin Ricaud, Department of Physics and Technology, UiT (internal member and leader of the committee)

Supervisors

  • Professor Robert Jenssen, Department of Physics and Technology, UiT (main supervisor)
  • Associate Prof. Michael C. Kampffmeyer, Department of Physics and Technology, UiT (co-supervisor)
  • Senior Researcher Arnt-Børre Salberg, Norwegian Computing Centre (co-supervisor)

Summary of thesis

Marine environment monitoring has become increasingly significant due to the excessive exploitation of oceans, which detrimentally impacts ecosystems. Deep learning provides an effective monitoring approach by automating the analysis of vast amounts of observed image data, enabling stakeholders to make informed decisions regarding fishing quotas or conservation efforts. The success of deep learning is often attributed to its capacity to extract relevant features from data, without the need for handcrafted rules or heuristics. However, this capability is not without limitations, as the intricate feature extraction process of deep learning-based systems poses fundamental challenges. A lack of annotated data presents an inherent challenge for deep learning. The widespread success of deep learning has primarily relied on the ample availability of annotated data, while deep learning models encounter difficulties when learning from limited annotations. However, obtaining annotated data is expensive, particularly in the context of marine environment monitoring, as it is often a manual process demanding the expertise of domain specialists. Another challenge of deep learning is a lack of explainability. The black-box nature of deep learning models can make it difficult to understand how they arrive at their decisions. This hinders their adoption in critical decision-making processes, as stakeholders may be hesitant to trust models whose decision-making rationale is not transparent or interpretable. To address the challenges and further advance deep learning methodologies, this thesis proposes three novel deep learning methods, highlighting marine environment monitoring as an application domain.

Link to thesis in Munin

Acknowledgement

The PhD project was a collaboration between Institute of Marine Research, The Norwegian computing center and UiT The Arctic University of Norway. The project was funded by COGMAR and Visual Intelligence.

Latest news

Three Visual Intelligence-authored papers accepted for leading AI conference on medical imaging

June 24, 2025

Visual Intelligence will be well represented at MICCAI 2025—one of the leading AI conferences on medical imaging and computer assisted intervention—with three recently accepted research papers.

2025 Norwegian AI Society Symposium: An insightful and collaborative event

June 23, 2025

More than 50 attendees from the Norwegian AI research community gathered in Tromsø, Norway for two days of insightful presentations, interactive technical sessions, and scientific and social interactions.

Minister of Research and Higher Education visits Visual Intelligence hub at Norwegian Computing Center

June 16, 2025

Last week, we wished Aasland—accompanied by Political Advisor Munir Jaber and Senior Adviser Finn-Hugo Markussen—welcome to the Norwegian Computing Center (NR). One of the visit's goals was to showcase ongoing Visual Intelligence projects at NR.

Visual Intelligence represented at EAGE Annual 2025

June 15, 2025

Alba Ordoñez and Anders U. Waldeland presented ongoing work on seismic foundation models and an interactive seismic interpretation engine at EAGE Annual 2025 in Toulouse, France.

Visual Intelligence PhD Fellow Eirik Østmo featured on Abels tårn

June 13, 2025

Østmo was invited to Abels tårn—one of the largest popular science radio shows in Norway—to answer listener-submitted questions related to artificial Intelligence (AI). The live show took place at Blårock Cafe in Tromsø, Norway on June 12th.

New Industrial PhD project with Kongsberg Satellite Services

June 12, 2025

VI industry partner Kongsberg Satellite Services (KSAT) received an Industrial PhD grant from the Research Council of Norway. The project will be closely connected to Visual Intelligence's "Earth observation" innovation area.

Visual Intelligence represented at plankton-themed workshop by The Institute of Marine Research

June 11, 2025

Visual Intelligence Researchers Amund Vedal and Arnt Børre Salberg recently presented ongoing Visual Intelligence research at a plankton-themed workshop organized by the Institute of Marine Research (IMR), Norway

My Research Stay at Visual Intelligence: Teresa Dorszewski

June 5, 2025

Teresa Dorszewski is a PhD Candidate at the Section for Cognitive Systems at the Technical University of Denmark. She visited Visual Intelligence in Tromsø from January to April 2025.

Visual Intelligence represented at the NORA Annual Conference 2025

June 3, 2025

Centre Director Robert Jenssen was invited to give a keynote and participate in a panel discussion on AI as critical national infrastructure at the NORA Annual Conference 2025 in Halden, Norway.

NRK.no: Nekter å svare om umerkede puslespill er KI-generert: – De bør være ærlige

June 2, 2025

Både forskere og statsråd mener kunstig intelligens bør tydelig merkes. Men forlaget som lager puslespillet som ekspertene mener er KI-generert, sier de ikke har noe med hvordan illustratører lager produktene sine (Norwegian news article by NRK)

ScienceNorway: This is how AI can contribute to faster treatment of lung cancer

May 30, 2025

Researchers have developed an artificial intelligence to map specific immune cells in lung cancer tumors. It can lead to less costly examinations and more personalised cancer treatment (English news story on sciencenorway.no).

Now Hiring: 4 PhD Fellows in Deep Learning

May 28, 2025

The Department of Physics and Technology at UiT The Arctic University of Norway is pleased to announce 4 exciting PhD Fellowships within machine learning at SFI Visual Intelligence. Application deadline: June 17th.

VG: Slik kan AI revolusjonere lungekreftbehandling

May 19, 2025

Norsk forskning har utviklet kunstig intelligens som raskt kan analysere lungekreft. Ekspertene forklarer hvordan dette kan bidra til en mer effektiv og persontilpasset behandling (Norwegian news article in vg.no)

Visual Intelligence evaluated by international experts: "The centre operates at an excellent level"

April 29, 2025

After four years of operation, an international AI expert panel was appointed to assess Visual Intelligence's progress and results. The evaluation was characterized by its excellent remarks on the centre's scientific quality and innovation output.

Visual Intelligence at Norsk Radiografforbund's mammography symposium

April 24, 2025

Senior Researcher Fredrik Dahl recently gave a talk about Norsk Regnesentral's work on developing AI algorithms for automatic analysis of image quality and cancer detection at Norsk Radiografforbund's mammography symposium in Oslo.