Related papers: IVOA Recommendation: HiPS - Hierarchical Progressi…

Geospatial big data plays a major role in the era of big data, as most data today are inherently spatial, collected with ubiquitous location-aware sensors. Efficiently collecting, managing, storing, and analyzing geospatial data streams…

While vision transformers show promise in numerous image restoration (IR) tasks, the challenge remains in efficiently generalizing and scaling up a model for multiple IR tasks. To strike a balance between efficiency and model capacity for a…

Hierarchical forecasting is a key problem in many practical multivariate forecasting applications - the goal is to simultaneously predict a large number of correlated time series that are arranged in a pre-specified aggregation hierarchy.…

Feature selection is an important tool to deal with high dimensional data. In unsupervised case, many popular algorithms aim at maintaining the structure of the original data. In this paper, we propose a simple and effective feature…

The ability to autonomously navigate in unknown environments is important for mobile robots. The map is the core component to achieve this. Most map representations rely on drift-free state estimation and provide a global metric map to…

Most of existing superpixel methods are designed to segment standard planar images as pre-processing for computer vision pipelines. Nevertheless, the increasing number of applications based on wide angle capture devices, mainly generating…

In the coming decade, astronomical surveys of the sky will generate tens of terabytes of images and detect hundreds of millions of sources every night. The study of these sources will involve computation challenges such as anomaly detection…

Hi-GAL, the Herschel infrared Galactic Plane Survey, is an Open Time Key Project of the Herschel Space Observatory. It will make an unbiased photometric survey of the inner Galactic Plane by mapping a two-degree wide strip in the longitude…

Whole-slide image analysis is essential for diagnostic tasks in pathology, yet existing deep learning methods primarily rely on flat classification, ignoring hierarchical relationships among class labels. In this study, we propose HiClass,…

Data exploration and visualization systems are of great importance in the Big Data era, in which the volume and heterogeneity of available information make it difficult for humans to manually explore and analyse data. Most traditional…

Hierarchical time-series forecasting (HTSF) is an important problem for many real-world business applications where the goal is to simultaneously forecast multiple time-series that are related to each other via a hierarchical relation.…

The Cambridge Infra-red Panoramic Survey Spectrograph (CIRPASS) is described. This near-infrared (NIR) spectrograph has been used on the 8m Gemini-South Telescope, the 3.9m Anglo-Australian Telescope (AAT) and the 4.2m William Herschel…

Vectorization process focus on grouping pixels of a raster image into raw line segments, and forming lines, polylines or poligons. To vectorize massive raster images regarding resource and performane problems, weuse a distributed HIPI image…

We present a 21cm line HI self-absorption (HISA) survey of cold atomic gas within Galactic longitudes 75 to 146 degrees and latitudes -3 to +5 degrees. We identify HISA as spatially and spectrally confined dark HI features and extract it…

Large, high-resolution space-based imaging surveys produce a volume of data that is difficult to present to the public in a comprehensible way. While megapixel-sized images can still be printed out or downloaded via the World Wide Web, this…

The lack of proper class discrimination among the Hyperspectral (HS) data points poses a potential challenge in HS classification. To address this issue, this paper proposes an optimal geometry-aware transformation for enhancing the…

The Rapid Imaging Planetary Spectrograph (RIPS) was designed as a long-slit high-resolution spectrograph for the specific application of studying atmospheres of spatially extended solar system bodies. With heritage in terrestrial airglow…

In Helio- and asteroseismology, it is important to have continuous, uninterrupted, data sets. However, seismic observations usually contain gaps and we need to take them into account. In particular, if the gaps are not randomly distributed,…

Ranking (or top-k) and skyline queries are the most popular approaches used to extract interesting data from large datasets. The first one is based on a scoring function to evaluate and rank tuples. Its computation is fast, but it is…

Aerial image registration or matching is a geometric process of aligning two aerial images captured in different environments. Estimating the precise transformation parameters is hindered by various environments such as time, weather, and…