Related papers: The web-PLOP observation prioritisation system

Ground-based observing time is precious in the era of exoplanet follow-up and characterization, especially in high-precision radial velocity instruments. Blind-search radial velocity surveys thus require a dedicated observational strategy…

Astronomers performing polarimetric analysis on astronomical images often have to manually identify locations on their objects of interest, such as galaxies, which exhibit the influence of magnetic forces due to interaction with their…

Predicting the motion of surrounding vehicles is key to safe autonomous driving, especially in unstructured environments without prior information. This paper proposes a novel online method to accurately predict the occupancy sets of…

Modern astronomical surveys such as the Large Synoptic Sky Survey (LSST) promise an unprecedented wealth of discoveries, delivered in the form of ~10 million alerts of time-variable events per night. Astronomers are faced with the daunting…

The surge of deep-space probes makes it unsustainable to navigate them with standard radiometric tracking. Self-driving interplanetary satellites represent a solution to this problem. In this work, a full vision-based navigation algorithm…

While microlensing is very rare, occurring on average once per million stars observed, current and near-future surveys are coming online with the capability of providing photometry of almost the entire visible sky to depths up to R ~ 22 mag…

Microlensing is the most promising method to study the statistical frequency of extra-solar planets orbiting typical (random) stars in the Milky Way, even those several kiloparsecs from Earth. The lensing zone corresponds to orbital…

With round-the-clock monitoring of galactic bulge microlensing events, the PLANET experiment constrains the abundance and can yield the discovery of planets down to the mass of earth around galactic disk and bulge stars. Data taken until…

Most existing star-galaxy classifiers depend on the reduced information from catalogs, necessitating careful data processing and feature extraction. In this study, we employ a supervised machine learning method (GoogLeNet) to automatically…

Among the group of extrasolar planets, transiting planets provide a great opportunity to obtain direct measurements for the basic physical properties, such as mass and radius of these objects. These planets are therefore highly important in…

In the context of human-robot interaction and collaboration scenarios, robotic grasping still encounters numerous challenges. Traditional grasp detection methods generally analyze the entire scene to predict grasps, leading to redundancy…

Among the methods proposed to detect extrasolar planets, microlensing is the only technique that can detect free-floating planets. Free-floating planets are detected through the channel of short-duration isolated lensing events. However, if…

The search for pulsars produces a massive amount of data which needs to be processed and analyzed. The limited speed of manual observation necessitates the involvement of large numbers of people to keep up with data collection. This paper…

We describe the Pan-STARRS Moving Object Processing System (MOPS), a modern software package that produces automatic asteroid discoveries and identifications from catalogs of transient detections from next-generation astronomical survey…

Amodal recognition is the ability of the system to detect occluded objects. Most SOTA Visual Recognition systems lack the ability to perform amodal recognition. Few studies have achieved amodal recognition through passive prediction or…

The Asteroid Terrestrial-impact Last Alert System (ATLAS) observes the visible sky every night in search of dangerous asteroids. With four soon five) sites ATLAS is facing new challenges for scheduling observations and linking detections to…

In this paper we consider a robot patrolling problem in which events arrive randomly over time at the vertices of a graph. When an event arrives it remains active for a random amount of time. If that time active exceeds a certain threshold,…

In this paper, we introduce machine learning approaches that are used to prioritize outpatients (OP) according to their current health state, resulting in self-optimizing heterogeneous networks (HetNet) that intelligently adapt according to…

Methods tackling multi-object tracking need to estimate the number of targets in the sensing area as well as to estimate their continuous state. While the majority of existing methods focus on data association, precise state (3D pose)…

We introduce the Online Preference Reporting and Aggregation (OPRA) system, an open-source online system that aims at providing support for group decision-making. We illustrate OPRA's distinctive features: UI for reporting rankings with…