Changkyu Choi introducing his Thesis.
Changkyu Choi defended his PhD thesis “Advancing Deep Learning for Marine Environment Monitoring” on June 9th 2023 at UiT The Arctic University of Norway.
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.
Evaluation Committee
Supervisors
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.
Our summer students have worked on projects related to fatigue and stress recognition with machine learning as their first research experience. Their results were presented at Georg Sverdrups hus at University of Oslo on October 16th 2024.
PhD candidate Rwiddhi Chakraborty recently gave an invited research talk titled "Perspectives on Multimodal Reasoning" at the Pioneer Centre for AI at University of Copenhagen.
Visual Intelligence was represented at Frampeik 2024 by associate professor Elisabeth Wetzer. The event gathered student researchers at Verdensteatret in Tromsø for discussions around AI-related topics.
Registration for the Northern Lights Deep Learning Conference 2025 is now open. The general deadline for registration is January 1st 2025.
We happily welcome Jan Zavadil, who recently started as a doctoral research fellow at Visual Intelligence in Tromsø in September 2024.
Visual Intelligence researchers participated in various dissemination activities throughout Forskningsdagene 2024. The activities aimed to disseminate general knowledge about deep learning and Visual Intelligence's research activities to the general public.
93 people from across the Visual Intelligence (VI) consortium gathered at Quality Airport Hotel Gardermoen for Visual Intelligence Days 2024, 24th to 25th of September.
Congratulations to Ghadi Al Hajj for successfully defending his PhD thesis and achieving the degree of Philosophiae Doctor at the University of Oslo on September 16th 2024!
Kommende søndag er det åpen dag på Nordnorsk vitensenter. Der lanseres vitensenteret siste nyvinning, en interaktiv utstilling basert på kunstig intelligens (KI).
Durgesh Kumar Singh is a PhD candidate at Visual Intelligence (VI) in Tromsø. He visited the University of Oslo and GE Vingmed Ultrasound from May to June 2024.
Maskinlæringsgruppen på UiT og SFI Visual Intelligence har arbeidet med å lage en utstilling som skal øke barns interesse, nysgjerrighet, og forståelse for kunstig intelligens. Nå vil den være utstillingsklar under et åpent familiearrangement på Nordnorsk vitensenter 22 september
Forskere har trent opp kunstig intelligens til å finne og kategorisere mikrofossiler. De tror arbeidet kan bli til stor nytte for geologer verden over (Norwegian news story at forskning.no).
Associate professor Kristoffer Wickstrøm represented Visual Intelligence at Nordnorsk ingeniørkonferanse 2024.
We happily welcome Christian Salomonsen, who recently started as a doctoral research fellow at Visual Intelligence in Tromsø.
I fremtiden kan leger og sykepleiere få hjelp av kunstig intelligens med å gjøre jobben sin. Men hvordan? En KI-forsker forklarer.
Associate professor and PI Elisabeth Wetzer participated in this year's Lindau Nobel Laureate Meeting in Vienna, Austria. The conference is one of the world's largest annual gatherings for Nobel Prize winners.
We happily welcome Preetraj Bhoodoo, who recently started as a doctoral research fellow at Visual Intelligence in Oslo.
Centre director Robert Jenssen was featured in an NRK Radio interview about the Arendalsuka event "Hvordan implementerer vi KI for bruk i helsesektoren på en trygg måte?"
Visual Intelligence was represented by director Robert Jenssen during the UiT event "Hvordan implementerer vi KI for bruk i helsesektoren på en trygg måte?". The event addressed how to safely implement artificial intelligence tools in the fields of health and medicine.
Director Robert Jenssen and postdoctoral research fellow Changkyu Choi represented Visual Intelligence at the Europe-Korea Conference on Science and Technology (EKC) 2024.