arxiv:2406.15503v1 [math.OC] 19 Jun 2024 Page 1 Data representation with optimal
transport Rocıo Dıaz Martın[0000−0002−3732−6296] and Ivan Vladimir Medri[0000−0003−2419−2193] …

We sought to develop new quantitative approaches to characterize the spatial distribution of
mammographic density and contrast enhancement of suspicious contrast-enhanced …

Deep convolutional neural networks (CNNs) are broadly considered to be state-of-the-art
generic end-to-end image classification systems. However, they are known to underperform …

Alterations in nuclear morphology are useful adjuncts and even diagnostic tools used by
pathologists in the diagnosis and grading of many tumors, particularly malignant tumors …

Low illumination face recognition is challenging as details are lacking due to lighting
conditions. Retinex theory points out that images can be divided into reflectance with color …

Here we describe a new image representation technique based on the mathematics of
transport and optimal transport. The method relies on the combination of the well-known …

Learning from point sets is an essential component in many computer vision and machine
learning applications. Native, unordered, and permutation invariant set structure space is …

Deep convolutional neural networks (CNNs) are broadly considered to be state-of-the-art
generic end-to-end image classification systems. However, they are known to underperform …

Posterior circulation stroke (PCS) presents significant diagnostic challenges due to poorly
localizing and non-specific symptoms, such as dizziness, nausea, and headache, which are …

Learning from point sets is an essential component in many computer vision and machine
learning applications. Native, unordered, and permutation invariant set structure space is …