相关论文: Automated crater detection on Mars using deep lear…

Existing multi-camera solutions for automatic scorekeeping in steel-tip darts are very expensive and thus inaccessible to most players. Motivated to develop a more accessible low-cost solution, we present a new approach to keypoint…

Many tasks require finding groups of elements in a matrix of numbers, symbols or class likelihoods. One approach is to use efficient bi- or tri-linear factorization techniques including PCA, ICA, sparse matrix factorization and plaid…

We formulate the lunar cratering distribution and verify the cratering asymmetries generated by the main-belt asteroids (MBAs) as well as the near-Earth objects (NEOs). Based on a planar model that excludes the terrestrial and lunar…

In this paper we show that Sun-viewing images obtained by the Mars Science Laboratory (MSL) Navigation Cameras (Navcam) can be used for retrieving the dust optical depth and constrain the aerosol physical properties at Gale Crater by…

Density functional theory (DFT) has become a standard tool for the study of point defects in materials. However, finding the most stable defective structures remains a very challenging task as it involves the solution of a multimodal…

We describe a computer application designed to analyze hyperspectral data collected by the Compact Infrared Spectrometer for Mars (CRISM). The application links the spectral, imaging and mapping perspectives on the eventual CRISM dataset by…

Diagnostic investigation has an important role in risk stratification and clinical decision making of patients with suspected and documented Coronary Artery Disease (CAD). However, the majority of existing tools are primarily focused on the…

This paper presents an novel object type classification method for automotive applications which uses deep learning with radar reflections. The method provides object class information such as pedestrian, cyclist, car, or non-obstacle. The…

While dark matter (DM) is the key ingredient for a successful theory of structure formation, its microscopic nature remains elusive. Indirect detection may provide a powerful test for some strongly motivated DM particle models.…

Deep learning has a great potential for estimating biomarkers in diffusion weighted magnetic resonance imaging (dMRI). Atlases, on the other hand, are a unique tool for modeling the spatio-temporal variability of biomarkers. In this paper,…

Identifying anatomical landmarks in 3D dental models is essential for orthodontic treatment, yet manual placement is labor-intensive and requires expert knowledge. While machine learning methods have been proposed for automatic landmark…

In computer vision, the estimation of the fundamental matrix is a basic problem that has been extensively studied. The accuracy of the estimation imposes a significant influence on subsequent tasks such as the camera trajectory…

Scientific imaging of the Moon, Mars, and other celestial bodies is often accomplished with pushbroom cameras. Craters with elliptical rims are common objects of interest within the images produced by such sensors. This work provides a…

With the progress of Mars exploration, numerous Mars image data are collected and need to be analyzed. However, due to the imbalance and distortion of Martian data, the performance of existing computer vision models is unsatisfactory. In…

Crater-Based Navigation (CBN) uses the ubiquitous impact craters of the Moon observed on images as natural landmarks to determine the six degrees of freedom pose of a spacecraft. To date, CBN has primarily been studied in the context of…

The paper explores the use of various machine learning methods to search for heterogeneous or atypical structures on astronomical maps. The study was conducted on the maps of the cosmic microwave background radiation from the Planck mission…

Near-surface wind fields on Mars are profoundly modulated by complex topography, yet fine-scale wind field characteristics remain poorly resolved for key geomorphological units such as deltas, valleys, and impact craters, due to the spatial…

Deep imaging programs, such as MATLAS which has just been completed at the CFHT, allows us to study with their diffuse light the outer stellar populations around large number of galaxies. We have carried out a systematic census of their…

Crystal structure prediction is one of the major unsolved problems in materials science. Traditionally, this problem is formulated as a global optimization problem for which global search algorithms are combined with first principle free…

One of the long-standing problems in materials science is how to predict a material's structure and then its properties given only its composition. Experimental characterization of crystal structures has been widely used for structure…