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Computer vision tasks such as image classification, image retrieval and few-shot learning are currently dominated by Euclidean and spherical embeddings, so that the final decisions about class belongings or the degree of similarity are made…

Image segmentation plays a critical role in unlocking the mysteries of the universe, providing astronomers with a clearer perspective on celestial objects within complex astronomical images and data cubes. Manual segmentation, while…

We have created a large database of similarity information between sub-regions of Hubble Space Telescope images. These data can be used to assess the accuracy of image search algorithms based on computer vision methods. The images were…

Object detection is one of the most fundamental yet challenging research topics in the domain of computer vision. Recently, the study on this topic in aerial images has made tremendous progress. However, complex background and worse imaging…

The wide availability of Commercial Off-The-Shelf (COTS) electronics that can withstand Low Earth Orbit conditions has opened avenue for wide deployment of CubeSats and small-satellites. CubeSats thanks to their low developmental and launch…

We present a two-component Machine Learning (ML) based approach for classifying astronomical images by data-quality via an examination of sources detected in the images and image pixel values from representative sources within those images.…

We summarize methods and plans to monitor and calibrate photometric observations with our autonomous, robotic network of 2m, 1m and 40cm telescopes. These are sited globally to optimize our ability to observe time-variable sources. Wide…

Geometric calibration of cameras and projectors is an essential step that must be performed before any imaging system can be used. There are many well-known geometric calibration methods for calibrating systems comprised of multiple…

The tightest cosmological constraints currently available are obtained by combining complementary data sets. When combining correlated data sets, various astrophysical biases that affect the measurements must be identified and treated.…

Being able to explore an environment and understand the location and type of all objects therein is important for indoor robotic platforms that must interact closely with humans. However, it is difficult to evaluate progress in this area…

Future missions, including the Habitable Worlds Observatory, will aim to image Earth-like exoplanets around Sun-like stars in reflected light. Determining whether an exoplanet is in the habitable zone of its star may be difficult in…

Robotic research encounters a significant hurdle when it comes to the intricate task of grasping objects that come in various shapes, materials, and textures. Unlike many prior investigations that heavily leaned on specialized point-cloud…

Context: Exoplanet science has made staggering progress in the last two decades, due to the relentless exploration of new detection methods and refinement of existing ones. Yet astrometry offers a unique and untapped potential of discovery…

Computational ghost imaging retrieves the spatial information of a scene using a single pixel detector. By projecting a series of known random patterns and measuring the back reflected intensity for each one, it is possible to reconstruct a…

We present a Bayesian algorithm to combine optical imaging of unresolved objects from distinct epochs and observation platforms for orbit determination and tracking. By propagating the non-Gaussian uncertainties we are able to optimally…

From a single image, visual cues can help deduce intrinsic and extrinsic camera parameters like the focal length and the gravity direction. This single-image calibration can benefit various downstream applications like image editing and 3D…

Humans perceive and construct the surrounding world as an arrangement of simple parametric models. In particular, man-made environments commonly consist of volumetric primitives such as cuboids or cylinders. Inferring these primitives is an…

The traceability of granite blocks consists in identifying each block with a finite number of color bands which represent a numerical code. This code has to be read several times throughout the manufacturing process, but its accuracy is…

Astronomical images and datasets are increasingly high-resolution and multi-dimensional. The vast majority of astronomers perform all of their visualisation and analysis tasks on low-resolution, two-dimensional desktop monitors. If there…

Recommendation systems based on image recognition could prove a vital tool in enhancing the experience of museum audiences. However, for practical systems utilizing wearable cameras, a number of challenges exist which affect the quality of…