Zobrazeno 1 - 10
of 121
pro vyhledávání: '"Paolo Napoletano"'
Autor:
Emanuele Aiello, Mirko Agarla, Diego Valsesia, Paolo Napoletano, Tiziano Bianchi, Enrico Magli, Raimondo Schettini
Publikováno v:
IEEE Access, Vol 12, Pp 65024-65031 (2024)
Large-scale self-supervised pretraining of deep learning models is known to be critical in several fields, such as language processing, where its has led to significant breakthroughs. Indeed, it is often more impactful than architectural designs. How
Externí odkaz:
https://doaj.org/article/00158747af4643a2aaac44e8708bc100
Publikováno v:
Remote Sensing, Vol 16, Iss 12, p 2079 (2024)
Hyperspectral pansharpening is crucial for the improvement of the usability of images in various applications. However, it remains underexplored due to a scarcity of data. The primary goal of pansharpening is to enhance the spatial resolution of hype
Externí odkaz:
https://doaj.org/article/887000b28b294063baa0649feccb1bce
Publikováno v:
Sensors, Vol 23, Iss 18, p 7876 (2023)
In this paper, different machine learning methodologies have been evaluated for the estimation of the multiple soil characteristics of a continental-wide area corresponding to the European region, using multispectral Sentinel-3 satellite imagery and
Externí odkaz:
https://doaj.org/article/eab17226c3314e7fa7ec077b692d03f0
Publikováno v:
Sensors, Vol 23, Iss 18, p 7893 (2023)
Defect segmentation of apples is an important task in the agriculture industry for quality control and food safety. In this paper, we propose a deep learning approach for the automated segmentation of apple defects using convolutional neural networks
Externí odkaz:
https://doaj.org/article/0c327ddc24e44188a7097f8975d498c9
Publikováno v:
Sensors, Vol 23, Iss 8, p 3788 (2023)
Precision agriculture has emerged as a promising approach to improve crop productivity and reduce the environmental impact. However, effective decision making in precision agriculture relies on accurate and timely data acquisition, management, and an
Externí odkaz:
https://doaj.org/article/21764bf326ae49c799bb26a46e84f339
Publikováno v:
IEEE Access, Vol 8, Pp 32003-32017 (2020)
State recognition of food images is a recent topic that is gaining a huge interest in the Computer Vision community. Recently, researchers presented a dataset of food images at different states where unfortunately no information regarding the food ca
Externí odkaz:
https://doaj.org/article/58c9e3dc0a144f6c804ff38335974a82
Publikováno v:
IEEE Access, Vol 8, Pp 32066-32079 (2020)
Recently, a significant amount of literature concerning machine learning techniques has focused on automatic recognition of activities performed by people. The main reason for this considerable interest is the increasing availability of devices able
Externí odkaz:
https://doaj.org/article/c2b0a89ca0d148d8bf8be1181a0ffb50
Autor:
Simone Bianco, Paolo Napoletano
Publikováno v:
IEEE Access, Vol 7, Pp 83581-83588 (2019)
In this paper, we address the problem of biometric recognition using the multimodal physiological signals. To this end, four different signals are considered: heart rate (HR), breathing rate (BR), palm electrodermal activity (P-EDA), and perinasal pe
Externí odkaz:
https://doaj.org/article/5c4df437ce42470d9ffb97f5e2d0de81
Publikováno v:
IEEE Access, Vol 7, Pp 173076-173085 (2019)
Filtering has been one of the main approaches to texture analysis since early on. Traditionally, the process involved designing the filters essentially by hand based on some prior knowledge (e.g. perceptual models, optimal mathematical properties, et
Externí odkaz:
https://doaj.org/article/9836fb3160fa4d4ab77a81e97ccf1137
Publikováno v:
IEEE Access, Vol 6, Pp 64270-64277 (2018)
This paper presents an in-depth analysis of the majority of the deep neural networks (DNNs) proposed in the state of the art for image recognition. For each DNN, multiple performance indices are observed, such as recognition accuracy, model complexit
Externí odkaz:
https://doaj.org/article/8fc3de29ba0a481db6757a76aa14f0bb