相关论文: Fast object detection for use onboard satellites

Machine learning is being widely applied to analyze satellite data with problems such as classification and feature detection. Unlike traditional image processing algorithms, geospatial applications need to convert the detected objects from…

Besides its major objective tuned to the detection of the stellar galactic population the Gaia mission experiment will also observe a large number of galaxies. In this work we intend to evaluate the number and the characteristics of the…

Upcoming next-generation sky surveys will detect large number of faint objects with magnitudes larger than 25. When objects are crowded within a limited a field of view, blending becomes unavoidable. Blending leads to the omission of many…

Deep B- and R-band CCD images of the central ~700 arcmin^2 of the Coma cluster core have been used to measure the dwarf-galaxy population in Coma. In this paper, we describe a newly developed code for automated detection, photometry and…

It is developed a very complex system (hardware/software) to detect luminosity variations connected with the discovery of new planets outside the Solar System. Traditional imaging approaches are very demanding in terms of computing time;…

Object detection algorithms for Lidar data have seen numerous publications in recent years, reporting good results on dataset benchmarks oriented towards automotive requirements. Nevertheless, many of these are not deployable to embedded…

Conducting surveillance of the Earth's orbit is a key task towards achieving space situational awareness (SSA). Our work focuses on the optical detection of man-made objects (e.g., satellites, space debris) in Geostationary orbit (GEO),…

Using simulated images, we test various methods, for the homogeneous detection of objects in DENIS images. The optimal detection limits depend on the object type and the sky background, but little on the PSF or the smoothing filter used to…

Object detection is a fundamental problem in computer vision, aiming at locating and classifying objects in image. Although current devices can easily take very high-resolution images, current approaches of object detection seldom consider…

Many algorithms have been proposed to help clinicians evaluate cone density and spacing, as these may be related to the onset of retinal diseases. However, there has been no rigorous comparison of the performance of these algorithms. In…

Limited by the performance factor, it is arduous to recognize target object and locate it in Augmented Reality (AR) scenes on low-end mobile devices, especially which using monocular cameras. In this paper, we proposed an algorithm which…

Taking a large amount of images, the Cassini Imaging Science Subsystem (ISS) has been routinely used in astrometry. In ISS images, disk-resolved objects often lead to false detection of stars that disturb the camera pointing correction. The…

We present results from a resolved stellar population search for dwarf satellite galaxies of six nearby (D $<5$ Mpc), sub-Milky-Way mass hosts using deep ($m\sim27$ mag) optical imaging from the Large Binocular Telescope. We perform image…

Satellite imagery is important for many applications including disaster response, law enforcement, and environmental monitoring. These applications require the manual identification of objects and facilities in the imagery. Because the…

Lidar has become an essential sensor for autonomous driving as it provides reliable depth estimation. Lidar is also the primary sensor used in building 3D maps which can be used even in the case of low-cost systems which do not use Lidar.…

OPTIMA is a small, versatile high-speed photometer which is primarily intended for time resolved observations of young high energy pulsars at optical wavelengths. The detector system consists of eight fiber fed photon counters based on…

The detection limit of astronomical imaging observations is limited by several noise sources. Some of that noise is correlated between neighbouring image pixels and exposures, so in principle could be learned and corrected. We present an…

In this paper, we present a novel approach to the estimation of strongly varying backgrounds in astronomical images by means of small objects removal and subsequent missing pixels interpolation. The method is based on the analysis of a…

Object detection is essential in space applications targeting Space Domain Awareness and also applications involving relative navigation scenarios. Current deep learning models for Object Detection in space applications are often trained on…

In this paper, we present a ship detection pipeline for low-cost medium resolution satellite optical imagery obtained from ESA Sentinel-2 and Planet Labs Dove constellations. This optical satellite imagery is readily available for any place…