SFI Visual Intelligence

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SFI Visual Intelligence is a Norwegian Center for Research-based Innovation that aims at unlocking the potential of visual intelligence across our main innov...

Latest Videos

Narratives of Possible AI Futures Fredrik Andreas Dahl (Norwegian Computing Center NR)

Perceptual Grouping and Adaptive Tokenisation Marius Aasan (SFI Visual Intelligence UiO)

Detecting, Tracking, and Identifying Birds and Bats at Wind Farms Mamoona Birkhez Shami (Spoor AI)

Sparse Tokens and Patch Representations Martine Hjelkrem Tan (University of Oslo)

Evaluating Concept-Based Robustness in Medical Image Analysis Valentina Corbetta

Explain It Robust Explanations for Classification, Clusters, and Outliers Ira Assent (Aarhus Uni.)

Self-Supervised Learning is Dead. Long Live Self-Supervised Learning Yuki Asano

Masked Autoencoding Enables Multimodal Learning for Environmental Sciences Devis Tuia (EPFL)

Echocardiography Foundation Models in Practice Preetraj Bhoodoo (University of Oslo)

LLM-Based Copilots and AI Agents Mihaela van der Schaar and Anders Boyd (The van der Schaar Lab)

Beyond Euclidean Deep Learning Aiden Durrant (University of Aberdeen)

Deep Learning Based Breast Cancer Risk Prediction from Longitudinal Mammograms Solveig Thrun (UiT)

Automated Methods for Efficient Training and Architecture Design Aaron Klein (OpenEuroLLM)

Ethical Challenges in Natural Language Processing Samia Touileb (University of Bergen)

Multimodal Learning Machine Learning Group (UiT The Arctic University of Norway)

Partially Supervised Multiple Retinal Disease Screening Boyi Zheng (University of Oulu)

Time Series Monitoring Using Vision Language Models Håkon Nese (Aker BP)

Tied Prototype Model for Few-Shot Medical Image Segmentation Hyeongji Kim (UiT)

The Role of Computational Pathology in Tomorrow’s Medicine Geert Litjens (Radboud University)

In Search of Hidden Talents Emergence in Foundation Model Oskar Skean (Unviersity of Kentucky)

Evaluating Foundation and Agentic Models in the Age of Trust Srishti Gautam (Microsoft)

Diffusion Model Meets XAI Counterfactual Generation for Model Debugging Nina Weng (DTU)

The Compression Paradox Why AI and Humans See the World Differently Ravid Shwartz Ziv

FM4CS A Versatile Foundation Model for Earth Observation Applications Arnt-Børre Salberg (NR)

Addressing Label Shift in Distributed Learning via Entropy Regularization Zhiyuan Wu (UiO)

Large Language Models Under the Hood Language Technology Group, UiO

Explainable Methods for Computer-Aided Diagnosis Anuja Vats (NTNU)

Responsible and Explainable Artificial Intelligence Virginia Dignum & Leila Methnani

Structure-Preserving Machine Learning for Physical Systems Sølve Eidnes (SINTEF Digital)

Aleatoric and Epistemic Uncertainty in Statistics and Machine Learning Willem Waegeman