reference radiance model and result data for an office building near LAX

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Loop closure detection helps simultaneous localization and mapping systems reduce map and state uncertainty via recognizing previously visited places along the path of a mobile robot. However, visual loop closure detection is susceptible to scenes with dyn ...

The application of digital technologies to historical newspapers has changed the research landscape historians were used to. An Eldorado? Despite undeniable advantages, the new digital affordance of historical newspapers also transforms research practices ...

Lightning is formed in the atmosphere through the combination of intricate dynamic and microphysical processes. Mainly due to this complexity, attempts to solve the important problem of lightning prediction have generally failed to yield accurate results. ...

Recent works in hand-object reconstruction mainly focus on the single-view and dense multi-view settings. On the one hand, single-view methods can leverage learned shape priors to generalise to unseen objects but are prone to inaccuracies due to occlusions ...

Machine learning has transformed many fields and has recently found applications in chemistry and materials science. The small datasets commonly found in chemistry sparked the development of sophisticated machine learning approaches that incorporate chemic ...

When enough annotated training data is available, supervised deep-learning. algorithms excel at estimating human body pose and shape using a single camera. The effects of too little such data being available can be mitigated by using other information sour ...

Data-driven techniques are increasingly used to replace electronic-structure calculations of matter. In this context, a relevant question is whether machine learning (ML) should be applied directly to predict the desired properties or combined explicitly w ...

Article Open Access Published: 08 November 2019 Nowcasting lightning occurrence from commonly available meteorological parameters using machine learning techniques Amirhossein Mostajabi, Declan L. Finney, Marcos Rubinstein & Farhad Rachidi npj Climate and ...

Efficiently querying multiple spatial data sets is a growing challenge for scientists. Astronomers query data sets that contain different types of stars (e.g., dwarfs, giants, stragglers) while neuroscientists query different data sets that model different ...

This repository contains microphysics routines, scripts, and processed data from the Weather Research and Forecasting (WRF) model simulations presented in the paper "RaFSIP: Parameterizing ice multiplication in models using a machine learning approach", by ...

Density, speed and energy efficiency of integrated circuits have been increasing exponentially for the last four decades following Moore's law. However, power and reliability pose several challenges to the future of technology scaling. Approximate computin ...

The response of local lightning to local surface temperature is examined near the Säntis mountain (2502 m ASL) in the eastern Swiss Alps during the first of the two hiatuses in global warming covering the time periods 1940-1972 and 1998-2014. The mountain ...

Increasing meteorological data availability and quality implies an adaptation of the interpolation methods for data combination. In this paper, we propose a new method to efficiently combine weather radar data with data from two heated rain gauge networks ...

With the increasing availability of both molecular and topo-climatic data, the main challenges facing landscape genomics — i.e. the combination of landscape ecology with population genomics — include processing large numbers of models and distinguishing be ...

Lattice codes used under the compute-and-forward paradigm suggest an alternative strategy for the standard Gaussian multiple-access channel (MAC): the receiver succes- sively decodes the integer linear combinations of the messages until it can invert and r ...

The first results of a campaign of intensive observation of precipitation in Dumont d'Urville, Antarctica, are presented. Several instruments collected data from November 2015 to February 2016 or longer, including a polarimetric radar (MXPol), a Micro Rain ...

Modern industrial, government, and academic organizations are collecting massive amounts of data at an unprecedented scale and pace. The ability to perform timely, predictable and cost-effective analytical processing of such large data sets in order to ext ...

Flood forecasting systems are today recognized as a key element in natural hazard mitigation. The objective is to exploit the available observed and forecasted meteorological information to foresee river discharges up to several days in advance, using a hy ...

Background:Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive p ...

Radon is a natural and radioactively well-known carcinogenic indoor air pollutant. Since 2020, a radon short-term proactive methodology has been proposed by Swiss authorities, which aims to evaluate the probability of overpassing the national reference val ...

reference radiance model and result data for an office building near LAX

Chat with Graph Search

PlaceNet: A multi-scale semantic-aware model for visual loop closure detection

Digitised Newspapers – A New Eldorado for Historians? Reflections on Tools, Methods and Epistemology

Augmenting the performance of impoverished sensor networks using machine learning and time reversal: Application to lightning nowcasting and location

Sparse multi-view hand-object reconstruction for unseen environments

Leveraging large language models for predictive chemistry

Using Motion Cues to Supervise Single-Frame Body Pose and Shape Estimation in Low Data Regimes

Electronic Excited States from Physically Constrained Machine Learning

Nowcasting lightning occurrence from commonly available meteorological parameters using machine learning techniques

Efficient Bundled Spatial Range Queries

Data and scripts for the RaFSIP scheme

Design of approximate and precision-scalable circuits for embedded multimedia and neural-network processing

An Analysis of Lightning Activity in the Säntis Region through the Big Hiatus in Global Warming

Spatial interpolation of precipitation from multiple rain gauge networks and weather radar data for operational applications in Alpine catchments

High performance computation of landscape genomic models including local indicators of spatial association

Gaussian Multiple Access via Compute-and-Forward

Measurements of precipitation in Dumont d'Urville, Adelie Land, East Antarctica

Toward timely, predictable and cost-effective data analytics

Los desafíos de la modelización hidrológica y la previsión de crecidas en tiempo real en alta montaña

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

Weather Impacts on Indoor Radon Short-Term Measurements in Switzerland