Zobrazeno 1 - 10
of 1 349
pro vyhledávání: '"Uricchio A"'
Autor:
Kristen Thane, Johanna Sonntag, Tobias Warnken, Dania Reiche, Cassandra Uricchio, Nicholas Frank
Publikováno v:
Journal of Veterinary Internal Medicine, Vol 38, Iss 6, Pp 3281-3287 (2024)
Abstract Background Testing for insulin dysregulation (ID) in horses is commonly performed to guide management and therapeutic strategies. Objectives To evaluate a newly developed glycemic pellets challenge (GPC) and compare results to those obtained
Externí odkaz:
https://doaj.org/article/b4bd6ceda6c94e6b82f918e0674b4459
Given the recent advances in multimodal image pretraining where visual models trained with semantically dense textual supervision tend to have better generalization capabilities than those trained using categorical attributes or through unsupervised
Externí odkaz:
http://arxiv.org/abs/2309.12110
Given a query composed of a reference image and a relative caption, the Composed Image Retrieval goal is to retrieve images visually similar to the reference one that integrates the modifications expressed by the caption. Given that recent research h
Externí odkaz:
http://arxiv.org/abs/2308.11485
Autor:
Francesca Ranieri, Gianfranco D’Onghia, Antonio Felice Uricchio, Ranieri Ada Cristina, Luigi Lopopolo, Ezio Ranieri
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-8 (2024)
Abstract An analysis of the pressure factors that influence the sustainable tourism in the Tremiti Islands (TI) has been performed. Tourist’s fluxes have been investigated in terms of monthly arrival and presences showing a high value of the territ
Externí odkaz:
https://doaj.org/article/81e4544f44034a2ca60a73e76f0e6d87
Publikováno v:
ICIAP 2022
In this paper, we introduced the novel concept of advisor network to address the problem of noisy labels in image classification. Deep neural networks (DNN) are prone to performance reduction and overfitting problems on training data with noisy annot
Externí odkaz:
http://arxiv.org/abs/2211.04177
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 6, Iss 2, Pp 1263-1280 (2024)
This is a systematic literature review of the application of machine learning (ML) algorithms in geosciences, with a focus on environmental monitoring applications. ML algorithms, with their ability to analyze vast quantities of data, decipher comple
Externí odkaz:
https://doaj.org/article/f1c0abd003814276954c7914b06fcbe8
Autor:
Raffaele Balsamo, Simone Tammaro, Biagio Barone, Felice Crocetto, Massimiliano Trivellato, Ferdinando Fusco, Stefano Domizio, Lorenzo Spirito, Carmelo Quattrone, Francesco Uricchio
Publikováno v:
Continence, Vol 10, Iss , Pp 101251- (2024)
Externí odkaz:
https://doaj.org/article/2435ec4d98ed44199363abcca6e64534
Autor:
Raffaele Balsamo, Simone Tammaro, Biagio Barone, Felice Crocetto, Massimiliano Trivellato, Ferdinando Fusco, Francesco Uricchio
Publikováno v:
Continence, Vol 10, Iss , Pp 101296- (2024)
Externí odkaz:
https://doaj.org/article/14bd92b55cd647fea4010682913c4929
Autor:
Alberto Biancardi, Annarita Colasante, Idiano D’Adamo, Cinzia Daraio, Massimo Gastaldi, Antonio Felice Uricchio
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-19 (2023)
Abstract Higher education institutions (HEIs), based on learning, innovation, and research, can support the progress of civil society. Many HEIs are implementing sustainability practices and projects to counteract climate change, often involving yout
Externí odkaz:
https://doaj.org/article/445312585d4e4d7da4d0bd58b0a5fbf4
To understand human behavior we must not just recognize individual actions but model possibly complex group activity and interactions. Hierarchical models obtain the best results in group activity recognition but require fine grained individual actio
Externí odkaz:
http://arxiv.org/abs/2105.06754