The increasing complexity and volume of financial transactions pose
significant challenges to traditional fraud detection systems. This technical
report investigates and compares the efficacy of classical, quantum, and
quantum-hybrid machine learni... read more
Underwater pollution is one of today's most significant environmental
concerns, with vast volumes of garbage found in seas, rivers, and landscapes
around the world. Accurate detection of these waste materials is crucial for
successful waste managem... read more
The advent of novel view synthesis techniques such as NeRF and 3D Gaussian
Splatting (3DGS) has enabled learning precise 3D models only from posed
monocular images. Although these methods are attractive, they hold two major
limitations that prevent... read more
Electrical Impedance Tomography (EIT) is a non-invasive medical imaging
method that reconstructs electrical conductivity mediums from boundary
voltage-current measurements, but its severe ill-posedness renders direct
operator learning with neural n... read more
BACKGROUND: While codes suffice for identifying stroke events in surveillance, accurately classifying stroke types and subtypes using electronic health records remains challenging due to limitations in structured data. This often necessitates manual... read more
Medical text embedding models are foundational to a wide array of healthcare
applications, ranging from clinical decision support and biomedical information
retrieval to medical question answering, yet they remain hampered by two
critical shortcomi... read more
Digital technologies and tools have transformed the way we can study cultural
heritage and the way we can recreate it digitally. Techniques such as laser
scanning, photogrammetry, and a variety of Mixed Reality solutions have enabled
researchers to... read more
Connected and software-defined vehicles promise to offer a broad range of
services and advanced functions to customers, aiming to increase passenger
comfort and support autonomous driving capabilities. Due to the high
reliability and availability r... read more
Understanding the decisions made by deep neural networks is essential in
high-stakes domains such as medical imaging and autonomous driving. Yet, these
models often lack transparency, particularly in computer vision.
Prototypical-parts-based neural... read more
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.