Zobrazeno 1 - 10
of 7 024
pro vyhledávání: '"A. Colantonio"'
Autor:
Carloni, Gianluca, Colantonio, Sara
The aim of this paper is threefold. We inform the AI practitioner about the human visual system with an extensive literature review; we propose a novel biologically motivated neural network for image classification; and, finally, we present a new plu
Externí odkaz:
http://arxiv.org/abs/2409.04360
Due to domain shift, deep learning image classifiers perform poorly when applied to a domain different from the training one. For instance, a classifier trained on chest X-ray (CXR) images from one hospital may not generalize to images from another h
Externí odkaz:
http://arxiv.org/abs/2408.04949
The graph coloring problem is an optimization problem involving the assignment of one of q colors to each vertex of a graph such that no two adjacent vertices share the same color. This problem is NP-hard and arises in various practical applications.
Externí odkaz:
http://arxiv.org/abs/2408.01503
Publikováno v:
BMC Research Notes, Vol 13, Iss 1, Pp 1-5 (2020)
Abstract Objective Non-native English speaking workers with a mild work-related traumatic brain and/or head injury are a vulnerable and underrepresented population in research studies. The researchers present their experiences with recruiting and per
Externí odkaz:
https://doaj.org/article/06798bae45a24f6e8b2ba6fa99a10f0e
Background and objective: Employing deep learning models in critical domains such as medical imaging poses challenges associated with the limited availability of training data. We present a strategy for improving the performance and generalization ca
Externí odkaz:
http://arxiv.org/abs/2403.17530
Human pose estimation, the process of identifying joint positions in a person's body from images or videos, represents a widely utilized technology across diverse fields, including healthcare. One such healthcare application involves in-bed pose esti
Externí odkaz:
http://arxiv.org/abs/2402.00700
Publikováno v:
BMC Public Health, Vol 17, Iss 1, Pp 1-8 (2017)
Abstract Background Work-related head injury is a critical public health issue due to its rising prevalence; the association with profound disruption of workers’ lives; and significant economic burdens in terms of medical costs and lost wages. Effo
Externí odkaz:
https://doaj.org/article/cd854780572649fb91d0ac9707ff54f2
Autor:
Pachetti, Eva, Colantonio, Sara
The lack of annotated medical images limits the performance of deep learning models, which usually need large-scale labelled datasets. Few-shot learning techniques can reduce data scarcity issues and enhance medical image analysis, especially with me
Externí odkaz:
http://arxiv.org/abs/2309.11433
Autor:
Carloni, Gianluca, Colantonio, Sara
We present a novel technique to discover and exploit weak causal signals directly from images via neural networks for classification purposes. This way, we model how the presence of a feature in one part of the image affects the appearance of another
Externí odkaz:
http://arxiv.org/abs/2309.10399
In this paper, we present a novel method to automatically classify medical images that learns and leverages weak causal signals in the image. Our framework consists of a convolutional neural network backbone and a causality-extractor module that extr
Externí odkaz:
http://arxiv.org/abs/2309.10725