Zobrazeno 1 - 10
of 698
pro vyhledávání: '"Malossi, A."'
Instance segmentation datasets play a crucial role in training accurate and robust computer vision models. However, obtaining accurate mask annotations to produce high-quality segmentation datasets is a costly and labor-intensive process. In this wor
Externí odkaz:
http://arxiv.org/abs/2402.16421
Neural Image Classifiers are effective but inherently hard to interpret and susceptible to adversarial attacks. Solutions to both problems exist, among others, in the form of counterfactual examples generation to enhance explainability or adversarial
Externí odkaz:
http://arxiv.org/abs/2310.00761
Low Noise Opto-Electro-Mechanical Modulator for RF-to-Optical Transduction in Quantum Communications
Autor:
Bonaldi, Michele, Borrielli, Antonio, Di Giuseppe, Giovanni, Malossi, Nicola, Morana, Bruno, Natali, Riccardo, Piergentili, Paolo, Sarro, Pasqualina Maria, Serra, Enrico, Vitali, David
Publikováno v:
Entropy 25(7), 1087 (2023)
In this work, we present an Opto-Electro-Mechanical Modulator (OEMM) for RF-to-optical transduction realized via an ultra-coherent nanomembrane resonator capacitively coupled to an rf injection circuit made of a microfabricated read-out able to impro
Externí odkaz:
http://arxiv.org/abs/2307.13049
Autor:
Hosaneide G. Araújo, Vitória V.F. Aquino, Luiz F.A. Pedrosa, Clebert J. Alves, Maria L.C.R. Silva, Vinícius L.R. Vilela, João P. Araújo Júnior, Camila D. Malossi, Carolina S.A.B. Santos, Sérgio S. Azevedo
Publikováno v:
Pesquisa Veterinária Brasileira, Vol 44 (2024)
ABSTRACT: The Caatinga biome is unique to Brazil, with unfavorable environmental characteristics for the survival of Leptospira spp. However, recent studies have shown high positivity at PCR (polymerase chain reaction) in small ruminants. There are n
Externí odkaz:
https://doaj.org/article/8be61af8ea0f4aef865e4e83d0d52a0b
Autor:
Kimmich, Maximilian, Bartezzaghi, Andrea, Bogojeska, Jasmina, Malossi, Cristiano, Vu, Ngoc Thang
Neural approaches have become very popular in Question Answering (QA), however, they require a large amount of annotated data. In this work, we propose a novel approach that combines data augmentation via question-answer generation with Active Learni
Externí odkaz:
http://arxiv.org/abs/2211.14880
Autor:
Frick, Thomas, Antognini, Diego, Rigotti, Mattia, Giurgiu, Ioana, Grewe, Benjamin, Malossi, Cristiano
Aging civil infrastructures are closely monitored by engineers for damage and critical defects. As the manual inspection of such large structures is costly and time-consuming, we are working towards fully automating the visual inspections to support
Externí odkaz:
http://arxiv.org/abs/2210.10586
Labeling images for visual segmentation is a time-consuming task which can be costly, particularly in application domains where labels have to be provided by specialized expert annotators, such as civil engineering. In this paper, we propose to use a
Externí odkaz:
http://arxiv.org/abs/2209.11159
Autor:
Márcia Furlan Nogueira, Camila Dantas Malossi, Maria Giulia Britto Frediani, David Pereira, Simone de Souza Prado, João Pessoa Araujo Jr., Cristiano Menezes
Publikováno v:
Sociobiology, Vol 71, Iss 2 (2024)
The occurrence of Colony Collapse Disorder (CCD) has prompted extensive research on the role of viruses, including Deformed Wing Virus (DWV), Acute Bee Paralysis Virus (ABPV), and Black Queen Cell Virus (BQCV), in honeybee health. This study investig
Externí odkaz:
https://doaj.org/article/d254ff09d1d3421ea98ebe251f830277
Autor:
de Araujo Santos, Julio Cesar, de Vasconcelos, Igor Felipe Ferreira, Nogueira, Denise Batista, Júnior, João Pessoa Araújo, Malossi, Camila Dantas, Santos, Carolina de Sousa Américo Batista, Alves, Clebert José, Silva, Maria Luana Cristiny Rodrigues, de Azevedo, Sérgio Santos
Publikováno v:
In Small Ruminant Research October 2024 239
Artificial Intelligence (AI) development is inherently iterative and experimental. Over the course of normal development, especially with the advent of automated AI, hundreds or thousands of experiments are generated and are often lost or never exami
Externí odkaz:
http://arxiv.org/abs/2202.10979