arXiv subjects

Carlo Donadio

Publications and source records attributed to Carlo Donadio.

3 recordsLinked to original sources

arXiv2025

AMBER -- Advanced SegFormer for Multi-Band Image Segmentation: an application to Hyperspectral Imaging

Deep learning has revolutionized the field of hyperspectral image (HSI) analysis, enabling the extraction of complex spectral and spatial features. While convolutional neural networks (CNNs) have been the backbone of HSI classification, their limitations in capturing global contextual features have led to the exploration of Vision Transformers (ViTs). This paper introduces AMBER, an advanced SegFormer specifically designed for multi-band image segmentation. AMBER enhances the original SegFormer by incorporating three-dimensional convolutions, custom kernel sizes, and a Funnelizer layer. This architecture enables processing hyperspectral data directly, without requiring spectral dimensionality reduction during preprocessing. Our experiments, conducted on three benchmark datasets (Salinas, Indian Pines, and Pavia University) and on a dataset from the PRISMA satellite, show that AMBER outperforms traditional CNN-based methods in terms of Overall Accuracy, Kappa coefficient, and Average Accuracy on the first three datasets, and achieves state-of-the-art performance on the PRISMA dataset. These findings highlight AMBER's robustness, adaptability to both airborne and spaceborne data, and its potential as a powerful solution for remote sensing and other domains requiring advanced analysis of high-dimensional data.

cs.CV↗

arXiv2021

A novel approach to the classification of terrestrial drainage networks based on deep learning and preliminary results on Solar System bodies

Several approaches were proposed to describe the geomorphology of drainage networks and the abiotic/biotic factors determining their morphology. There is an intrinsic complexity of the explicit qualification of the morphological variations in response to various types of control factors and the difficulty of expressing the cause-effect links. Traditional methods of drainage network classification are based on the manual extraction of key characteristics, then applied as pattern recognition schemes. These approaches, however, have low predictive and uniform ability. We present a different approach, based on the data-driven supervised learning by images, extended also to extraterrestrial cases. With deep learning models, the extraction and classification phase is integrated within a more objective, analytical, and automatic framework. Despite the initial difficulties, due to the small number of training images available, and the similarity between the different shapes of the drainage samples, we obtained successful results, concluding that deep learning is a valid way for data exploration in geomorphology and related fields.

physics.geo-ph↗

arXiv2020

Refining the Uluzzian through a new lithic assemblage from Roccia San Sebastiano (Mondragone, southern Italy)

Roccia San Sebastiano is a tectonic-karstic cave located at the foot of the southern slope of Mt. Massico, in the territory of Mondragone (Caserta) in Campania (southern Italy). Systematic excavation has been carried out since 2001, leading to the partial exploration of an important Pleistocene deposit, extraordinarily rich in lithic and faunal remains. The aim of this paper is to (1) present the stratigraphic sequence of Roccia San Sebastiano, and (2) technologically describe the lithic materials of squares F14 t18, t19, t20; E16 t16, t17, t18 recently recognised as Uluzzian. The stratigraphic sequence is more than 3 metres thick and dates from the Middle to the Upper Palaeolithic. It contains different techno-complexes: Gravettian, Aurignacian, Uluzzian and Mousterian. In the Uluzzian lithic assemblage mostly local pebbles of chert were used in order to produce small-sized objects. The concept of debitage mainly deals with unidirectional debitage with absent or fairly accurate management of the convexities and angles; the striking platforms are usually natural or made by one stroke. It is attested the use of both direct freehand percussion and bipolar technique on anvil in the same reduction sequence. Amongst the retouched tools the presence of two lunates is of note. This study of the Roccia San Sebastiano Uluzzian lithic complexes is significant for understanding the dynamics of the transition from Middle to Upper Palaeolithic in the Tyrrhenian margin of southern Italy.

q-bio.PE↗