4 research outputs found
The high-resolution map of Oxia Planum, Mars; the landing site of the ExoMars Rosalind Franklin rover mission
This 1:30,000 scale geological map describes Oxia Planum, Mars, the landing site for the ExoMars Rosalind Franklin rover mission. The map represents our current understanding of bedrock units and their relationships prior to Rosalind Franklinâs exploration of this location. The map details 15 bedrock units organised into 6 groups and 7 textural and surficial units. The bedrock units were identified using visible and near-infrared remote sensing datasets. The objectives of this map are (i) to identify where the most astrobiologically relevant rocks are likely to be found, (ii) to show where hypotheses about their geological context (within Oxia Planum and in the wider geological history of Mars) can be tested, (iii) to inform both the long-term (hundreds of metres to âŒ1â
km) and the short-term (tens of metres) activity planning for rover exploration, and (iv) to allow the samples analysed by the rover to be interpreted within their regional geological context
30-m HRSC DTM Mosaic of Gale Crater, Mars
Digital terrain model (DTM) mosaic of Gale crater, Mars, processed from High-Resolution Stereo Camera (HRSC) stereo images using the modification of DLR-VICAR described by Kim and Muller (2009).
Format: GeoTiff
Projection: Equidistant cylindrical
Datum: Spheroid (r = 3396.190 km)
Bit depth: Float32
Grid-spacing: 30 m/pixel
Terrain reference: 200-m MOLA and HRSC blended global DTM (Fergason et al. 2018)
HRSC source images: H1938_0000, H1927_0000, and H1916_0000The first author is now at Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California. Contact: [email protected]
CLASSIFICATION OF CANE SUGAR BASED ON IMAGE PROCESSING AND ARTIFICIAL NEURAL NETWORK
Classification and identification of agricultural products are usually done
manually. This method is prone to error and subjectivity of the user. The other
method, laboratory testing, can only be done by professional and takes time.
Classification and identification of cane sugar in Indonesia is also done with
similar process with no standardization. In the production of cane sugar, several
stages and condition produce different kinds of sugar, resulting in the need of
supervision. In automation and standardization of quality, quantized identification
process needs to be done. System was designed as Artificial Neural Network with
one hidden layer using Levenberg-Marquardt algorithm. Colour and textural
features were extracted from 120 images of cane sugar for Artificial Neural
Network inputs. After feature reduction, the designed system could identify 8 kinds
of cane sugar with success rate of 85%. Designed system was also tested for
different learning rate, activating function, ratio of training and testing set and
different testing conditions. Application with GUI was also made for user
The high-resolution map of Oxia Planum, Mars; the landing site of the ExoMars Rosalind Franklin rover mission
International audienceThis 1:30,000 scale geological map describes Oxia Planum, Mars, the landing site for theExoMars Rosalind Franklin rover mission. The map represents our current understanding ofbedrock units and their relationships prior to Rosalind Franklinâs exploration of this location.The map details 15 bedrock units organised into 6 groups and 7 textural and surficial units.The bedrock units were identified using visible and near-infrared remote sensing datasets.The objectives of this map are (i) to identify where the most astrobiologically relevant rocksare likely to be found, (ii) to show where hypotheses about their geological context (withinOxia Planum and in the wider geological history of Mars) can be tested, (iii) to inform boththe long-term (hundreds of metres to âŒ1 km) and the short-term (tens of metres) activityplanning for rover exploration, and (iv) to allow the samples analysed by the rover to beinterpreted within their regional geological context