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Recent applications in computer vision have come to heavily rely on superpixel over-segmentation as a pre-processing step for higher level vision tasks, such as object recognition, image labelling or image segmentation. Here we present a…
Informative path planning is an important and challenging problem in robotics that remains to be solved in a manner that allows for wide-spread implementation and real-world practical adoption. Among various reasons for this, one is the…
We present a Bayesian hierarchical framework for a principled data analysis pipeline of peculiar velocity surveys, which makes explicit the inference problem of constraining cosmological parameters from redshift-independent distance…
Topographic laser scanning is a remote sensing method to create detailed 3D point cloud representations of the Earth's surface. Since data acquisition is expensive, simulations can complement real data given certain premises are available:…
We study informative path planning (IPP) with travel budgets in cluttered environments, where an agent collects measurements of a latent field modeled as a Gaussian process (GP) to reduce uncertainty at target locations. Graph-based solvers…
State-of-the-art techniques proposed for 6D object pose recovery depend on occlusion-free point clouds to accurately register objects in 3D space. To reduce this dependency, we introduce a novel architecture called Iterative Hough Forest…
The survey speed of ASKAP makes it a prime instrument with which to survey the HI universe, enabling it to carry out both wide surveys of the entire sky, as well as deep surveys covering cosmologically representative volumes. Here, the use…
The rapid growth of imaging and spectroscopic surveys has intensified the need for efficient tools that support visual inspection, a practice that remains essential for tasks such as classification, catalog refinement, and validation of…
We propose a flexible and multi-scale method for organizing, visualizing, and understanding datasets sampled from or near stratified spaces. The first part of the algorithm produces a cover tree using adaptive thresholds based on a…
Positioning systems and frameworks use various techniques to determine the position of an object. Some of the existing solutions combine different sensory data at the time of positioning in order to compute more accurate positions by…
We describe the production and verification of sky maps of the five SPIRE fields observed as part of the Herschel Multi-tiered Extragalactic Survey (HerMES) during the Science Demonstration Phase (SDP) of the Herschel mission. We have…
In this paper, we present Hi-D maps, a novel method for the visualization of multi-dimensional categorical data. Our work addresses the scarcity of techniques for visualizing a large number of data-dimensions in an effective and…
Advanced Hyperspectral Data Analysis Software (AVHYAS) plugin is a python3 based quantum GIS (QGIS) plugin designed to process and analyse hyperspectral (Hx) images. It is developed to guarantee full usage of present and future Hx airborne…
HIRES processing provides a significant improvement in both resolution and image quality over previous IRAS image products, but the characteristics of the HIRES beam make accurate comparisons between the various IRAS bandpasses and between…
In this work, we present a novel dense-correspondence method for 6DoF object pose estimation from a single RGB-D image. While many existing data-driven methods achieve impressive performance, they tend to be time-consuming due to their…
The rapid advancement of artificial intelligence and widespread use of smartphones have resulted in an exponential growth of image data, both real (camera-captured) and virtual (AI-generated). This surge underscores the critical need for…
In this paper we describe the architecture of a Platform as a Service (PaaS) oriented to computing and data analysis. In order to clarify the choices we made, we explain the features using practical examples, applied to several known usage…
Most existing Siamese-based tracking methods execute the classification and regression of the target object based on the similarity maps. However, they either employ a single map from the last convolutional layer which degrades the…
The rapid development of large climate models has created the requirement of storing and transferring massive atmospheric data worldwide. Therefore, data compression is essential for meteorological research, but an efficient compression…
Web browsers are increasingly used as middleware platforms offering a central access point for service provision. Using backend containerization, RESTful APIs, and distributed computing allows for complex systems to be realized that address…