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An overview of the inputs for each step in our processing pipeline. a) A region in the HiRISE image of ESP 018707 2205 is shown at the native resolution (0.3m/px) with a blue box highlighting the window size for our classifier network. b) A 256 x 256 pixel window is used as input for our spatial classifier algorithm however the window is at 1/16 the original resolution (1.2m/px). A grid of 8x8 squares is displayed showing how that image gets tiled and preprocessed using parts of a JPEG encoder which involves the discrete cosine transform (d). c) A single 8x8 tile flattened into a 1d array which is used for the DCT transform (d). e) A block of Fourier coefficients is rearranged into a data cube and used as input for our Fourier classifier. Reducing the image size and ultimately the channel size after the first conv. layer significantly shortens the network’s processing time compared to the spatial image input. -- astro-ph.EP

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Mapping “Brain Coral” Regions On Mars Using Deep Learning

by Keith CowingNovember 22, 2023November 22, 2023

One of the main objectives of the Mars Exploration Program is to search for evidence of past or current life on the planet. To achieve this, Mars exploration has been […]

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Mapping “Brain Coral” Regions On Mars Using Deep Learning

Inspecting A Dragonfly Mass Spectrometer (DRAMS) Transducer

NASA Explores Potential Commercial Servicing for Hubble Telescope

The Fate of Ice Sheets on Near-Synchronously Rotating Land Planets

Extraterrestrial Chemical Boundary Conditions and Evolutionary Opportunity Space on Early Earth

Complex Organic Molecules in Protostars with ALMA Spectral Surveys (COMPASS) III. CH3OH isotopic fractionation in the low-mass protostar BHR71-IRS1