Zobrazeno 1 - 10
of 321
pro vyhledávání: '"A. Traviglia"'
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVIII-M-2-2023, Pp 557-562 (2023)
Preserving historical archival heritage involves not only physical measures to safeguard these valuable texts but also providing for their digital preservation. However, merely digitising manuscripts and codexes is not enough. A further step is neede
Externí odkaz:
https://doaj.org/article/8b7849e83aa3483983ced62a9cc741fb
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVIII-M-2-2023, Pp 995-1000 (2023)
This paper introduces a novel methodology developed for creating 3D models of archaeological artifacts that reduces the time and effort required by operators. The approach uses a simple vision system mounted on a robotic arm that follows a predetermi
Externí odkaz:
https://doaj.org/article/befaa5b8031641619b26a5e694d9c9c5
The primary challenge for handwriting recognition systems lies in managing long-range contextual dependencies, an issue that traditional models often struggle with. To mitigate it, attention mechanisms have recently been employed to enhance context-a
Externí odkaz:
http://arxiv.org/abs/2409.05699
Autor:
Jaturapitpornchai, Raveerat, Poggi, Giulio, Sech, Gregory, Kokalj, Ziga, Fiorucci, Marco, Traviglia, Arianna
Publikováno v:
IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
Deep learning methods in LiDAR-based archaeological research often leverage visualisation techniques derived from Digital Elevation Models to enhance characteristics of archaeological objects present in the images. This paper investigates the impact
Externí odkaz:
http://arxiv.org/abs/2404.05512
Publikováno v:
IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
Hyperspectral data recorded from satellite platforms are often ill-suited for geo-archaeological prospection due to low spatial resolution. The established potential of hyperspectral data from airborne sensors in identifying archaeological features h
Externí odkaz:
http://arxiv.org/abs/2404.05447
Publikováno v:
2023 Sixth International Workshop on Mobile Terahertz Systems (IWMTS), Bonn, Germany, 2023, pp. 1-5
Terahertz time-domain spectroscopy (THz-TDS) employs sub-picosecond pulses to probe dielectric properties of materials giving as a result a 3-dimensional hyperspectral data cube. The spatial resolution of THz images is primarily limited by two source
Externí odkaz:
http://arxiv.org/abs/2312.13820
Identifying changes in a pair of 3D aerial LiDAR point clouds, obtained during two distinct time periods over the same geographic region presents a significant challenge due to the disparities in spatial coverage and the presence of noise in the acqu
Externí odkaz:
http://arxiv.org/abs/2307.15428
Autor:
Sech, Gregory, Soleni, Paolo, der Vaart, Wouter B. Verschoof-van, Kokalj, Žiga, Traviglia, Arianna, Fiorucci, Marco
When applying deep learning to remote sensing data in archaeological research, a notable obstacle is the limited availability of suitable datasets for training models. The application of transfer learning is frequently employed to mitigate this drawb
Externí odkaz:
http://arxiv.org/abs/2307.03512
Publikováno v:
In: Image Analysis and Processing. ICIAP 2022 Workshops. Lecture Notes in Computer Science, vol. 13373. Springer, Cham (2022)
Most computer vision and machine learning-based approaches for historical document analysis are tailored to grayscale or RGB images and thus, mostly exploit their spatial information. Multispectral (MS) and hyperspectral (HS) images contain, next to
Externí odkaz:
http://arxiv.org/abs/2303.05130
This paper proposes JiGAN, a GAN-based method for solving Jigsaw puzzles with eroded or missing borders. Missing borders is a common real-world situation, for example, when dealing with the reconstruction of broken artifacts or ruined frescoes. In th
Externí odkaz:
http://arxiv.org/abs/2203.14428