Related papers: The Observed Inclination Problem: Solved at Last?
Visually impaired individuals rely heavily on accurate and timely information about obstacles and their surrounding environments to achieve independent living. In recent years, significant progress has been made in the development of…
We provide first the functional analysis background required for reduced order modeling and present the underlying concepts of reduced basis model reduction. The projection-based model reduction framework under affinity assumptions,…
External occulters, otherwise known as starshades, have been proposed as a solution to one of the highest priority yet technically vexing problems facing astrophysics - the direct imaging and characterization of terrestrial planets around…
One of the key-points for the future developments of the multiconjugate adaptive optics for the astronomy is the availability of the correction for a large fraction of the sky. The sky coverage represents one of the limits of the existing…
Autonomous vehicle (AV) systems rely on robust perception models as a cornerstone of safety assurance. However, objects encountered on the road exhibit a long-tailed distribution, with rare or unseen categories posing challenges to a…
The rapid emergence of airborne platforms and imaging sensors are enabling new forms of aerial surveillance due to their unprecedented advantages in scale, mobility, deployment and covert observation capabilities. This paper provides a…
Atmospheric powered descent guidance can be solved by successive convexification; however, its onboard application is impeded by the sharp increase in computation caused by nonlinear aerodynamic forces. The problem has to be converted into…
We study image inpainting with generative diffusion models. Existing methods typically either train dedicated task-specific models, or adapt a pretrained diffusion model separately for each masked image at deployment. We introduce a…
A new method for improving the resolution of astronomical images is presented. It is based on the principle that sampled data cannot be fully deconvolved without violating the sampling theorem. Thus, the sampled image should not be…
Current methods for Earth observation tasks such as semantic mapping, map alignment, and change detection rely on near-nadir images; however, often the first available images in response to dynamic world events such as natural disasters are…
Aerial scene classification, which aims to automatically label an aerial image with a specific semantic category, is a fundamental problem for understanding high-resolution remote sensing imagery. In recent years, it has become an active…
Category-level articulated object pose estimation focuses on the pose estimation of unknown articulated objects within known categories. Despite its significance, this task remains challenging due to the varying shapes and poses of objects,…
Large area surveys will dominate the forthcoming decades of astronomy and their success requires characterizing thousands of discoveries through additional observations at higher spatial or spectral resolution, and at complementary cadences…
Object detection on the edge (Edge-OD) is in growing demand thanks to its ever-broad application prospects. However, the development of this field is rigorously restricted by the deployment dilemma of simultaneously achieving high accuracy,…
This paper is based on the opening lecture given at the 2017 edition of the Evry Schatzman school on high-angular resolution imaging of stars and their direct environment. Two relevant observing techniques: long baseline interferometry and…
Far-infrared astronomy has advanced rapidly since its inception in the late 1950's, driven by a maturing technology base and an expanding community of researchers. This advancement has shown that observations at far-infrared wavelengths are…
We propose a new method for solving an important problem of astronomy that arises in observations with ultrahigh-angular-resolution interferometers. This method is based on the application of the theory of artificial neural networks. We…
Given two object images, how can we explain their differences in terms of the underlying object properties? To address this question, we propose Align-Deform-Subtract (ADS) -- an interventional framework for explaining object differences.…
As members of the instrument team for the Advanced CCD Imaging Spectrometer (ACIS) on NASA's Chandra X-ray Observatory and as Chandra General Observers, we have developed a wide variety of data analysis methods that we believe are useful to…
We present a novel artificial diffusion method to circumvent the instabilities associated with the standard finite element approximation of convection-diffusion equations. Motivated by the micromorphic approach, we introduce an auxiliary…