Search results for " Computer vision"
showing 10 items of 352 documents
La logica visiva dei data
2020
I deal with visuals, and I would like to show how, starting out from the visual aspect as a key element of Western society, we may attempt to understand how digitality (both in terms of technology and thought) has brought about revolutionary change in our society, altering cultural, social, and economic paradigms... I would also like to show how the archive, and all that may be understood as such, has become the cultural logic of our time, in the form of the database.
Pd/Au/SiC Nanostructured Diodes for Nanoelectronics: Room Temperature Electrical Properties
2010
Pd/Au/SiC nanostructured Schottky diodes were fabricated embedding Au nanoparticles (NPs) at the metalsemiconductor interface of macroscopic Pd/SiC contacts. The Au NPs mean size was varied controlling the temperature and time of opportune annealing processes. The electrical characteristics of the nanostructured diodes were studied as a function of the NPs mean size. In particular, using the standard theory of thermoionic emission, we obtained the effective Schottky barrier height (SBH) and the effective ideality factor observing their dependence on the annealing time and temperature being the signature of their dependence on the mean NP size. Furthermore, plotting the effective SBH as a fu…
Active Learning Methods for Efficient Hybrid Biophysical Variable Retrieval
2016
Kernel-based machine learning regression algorithms (MLRAs) are potentially powerful methods for being implemented into operational biophysical variable retrieval schemes. However, they face difficulties in coping with large training data sets. With the increasing amount of optical remote sensing data made available for analysis and the possibility of using a large amount of simulated data from radiative transfer models (RTMs) to train kernel MLRAs, efficient data reduction techniques will need to be implemented. Active learning (AL) methods enable to select the most informative samples in a data set. This letter introduces six AL methods for achieving optimized biophysical variable estimat…
Toward a Collective Agenda on AI for Earth Science Data Analysis
2021
In the last years we have witnessed the fields of geosciences and remote sensing and artificial intelligence to become closer. Thanks to both the massive availability of observational data, improved simulations, and algorithmic advances, these disciplines have found common objectives and challenges to advance the modeling and understanding of the Earth system. Despite such great opportunities, we also observed a worrying tendency to remain in disciplinary comfort zones applying recent advances from artificial intelligence on well resolved remote sensing problems. Here we take a position on research directions where we think the interface between these fields will have the most impact and be…
Multi-temporal and Multi-source Remote Sensing Image Classification by Nonlinear Relative Normalization
2016
Remote sensing image classification exploiting multiple sensors is a very challenging problem: data from different modalities are affected by spectral distortions and mis-alignments of all kinds, and this hampers re-using models built for one image to be used successfully in other scenes. In order to adapt and transfer models across image acquisitions, one must be able to cope with datasets that are not co-registered, acquired under different illumination and atmospheric conditions, by different sensors, and with scarce ground references. Traditionally, methods based on histogram matching have been used. However, they fail when densities have very different shapes or when there is no corres…
Signal reconstruction, modeling and simulation of a vehicle full-scale crash test based on Morlet wavelets
2012
Creating a mathematical model of a vehicle crash is a task which involves considerations and analysis of different areas which need to be addressed because of the mathematical complexity of a crash event representation. Therefore, to simplify the analysis and enhance the modeling process, in this paper a novel wavelet-based approach is introduced to reproduce acceleration pulse of a vehicle involved in a crash event. The acceleration of a colliding vehicle is measured in its center of gravity-this crash pulse contains detailed information about vehicle behavior throughout a collision. Three types of signal analysis are elaborated here: time domain analysis (i.e. description of kinematics of…
The Large Area Detector onboard the eXTP mission
2018
The eXTP (enhanced X-ray Timing and Polarimetry) mission is a major project of the Chinese Academy of Sciences (CAS) and China National Space Administration (CNSA) currently performing an extended phase A study and proposed for a launch by 2025 in a low-earth orbit. The eXTP scientific payload envisages a suite of instruments (Spectroscopy Focusing Array, Polarimetry Focusing Array, Large Area Detector and Wide Field Monitor) offering unprecedented simultaneous wide-band X-ray spectral, timing and polarimetry sensitivity. A large European consortium is contributing to the eXTP study and it is expected to provide key hardware elements, including a Large Area Detector (LAD). The LAD instrumen…
The Cryogenic AntiCoincidence detector for ATHENA: the progress towards the final pixel design
2014
“The Hot and Energetic Universe” is the scientific theme approved by the ESA SPC for a Large mission to be flown in the next ESA slot (2028th) timeframe. ATHENA is a space mission proposal tailored on this scientific theme. It will be the first X-ray mission able to perform the so-called “Integral field spectroscopy”, by coupling a high-resolution spectrometer, the X-ray Integral Field Unit (X-IFU), to a high performance optics so providing detailed images of its field of view (5’ in diameter) with an angular resolution of 5” and fine energy-spectra (2.5eV@E<7keV). The X-IFU is a kilo-pixel array based on TES (Transition Edge Sensor) microcalorimeters providing high resolution spectroscopy …
Surface soil water content estimation based on thermal inertia and Bayesian smoothing
2014
Soil water content plays a critical role in agro-hydrology since it regulates the rainfall partition between surface runoff and infiltration and, the energy partition between sensible and latent heat fluxes. Current thermal inertia models characterize the spatial and temporal variability of water content by assuming a sinusoidal behavior of the land surface temperature between subsequent acquisitions. Such behavior implicitly supposes clear sky during the whole interval between the thermal acquisitions; but, since this assumption is not necessarily verified even if sky is clear at the exact epoch of acquisition, , the accuracy of the model may be questioned due to spatial and temporal varia…
New stage-discharge relationship for inclined non-rectangular weirs
2018
Abstract In this paper, the outflow process of inclined non-rectangular weirs is studied applying the dimensional analysis and the incomplete self-similarity theory. At first, a new stage-discharge equation, applicable for the non-rectangular weirs having a different geometrical shape (parabolic, semicircular, inverted semicircular), is theoretically deduced using a characteristic width. Then, this power stage-discharge relationship (Eq. (17) ) is calibrated and tested using measurements carried out by Raiknar for parabolic, semicircular and inverted semicircular weirs having different inclination respect to the vertical (10°, 20°, 30°, 40° and 45°). For each geometrical shape, the analysis…