118 citations · 138 across the 5 of their papers we have counts for
6 papers
MIL-PF: Multiple Instance Learning on Precomputed Features for Mammography Classification
Nikola Jovišić, Milica Škipina, Nicola Dall'Asen +1
Modern foundation models provide highly expressive visual representations, yet adapting them to high-resolution medical imaging remains challenging due to limited annotations and w…
MAMBO: High-Resolution Generative Approach for Mammography Images
Milica Škipina, Nikola Jovišić, Nicola Dall'Asen +5
Mammography is the gold standard for the detection and diagnosis of breast cancer. This procedure can be significantly enhanced with Artificial Intelligence (AI)-based software, wh…
CERN for AI: A Theoretical Framework for Autonomous Simulation-Based Artificial Intelligence Testing and Alignment
Ljubisa Bojic, Matteo Cinelli, Dubravko Culibrk +1
This paper explores the potential of a multidisciplinary approach to testing and aligning artificial intelligence (AI), specifically focusing on large language models (LLMs). Due t…
Identifying Individual Dogs in Social Media Images
Djordje Batic, Dubravko Culibrk
We present the results of an initial study focused on developing a visual AI solution able to recognize individual dogs in unconstrained (wild) images occurring on social media. Th…
Self Paced Deep Learning for Weakly Supervised Object Detection
Enver Sangineto, Moin Nabi, Dubravko Culibrk +1
In a weakly-supervised scenario object detectors need to be trained using image-level annotation alone. Since bounding-box-level ground truth is not available, most of the solution…
Unveiling Spatial Epidemiology of HIV with Mobile Phone Data
Sanja Brdar, Katarina Gavric, Dubravko Culibrk +1
An increasing amount of geo-referenced mobile phone data enables the identification of behavioral patterns, habits and movements of people. With this data, we can extract the knowl…