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We present a deep learning, computer vision algorithm constructed for the purposes of identifying and classifying charged particles in camera image sensors. We apply our algorithm to data collected by the Distributed Electronic Cosmic-ray Observatory (DECO), a global network of smartphones that monitors camera image sensors for the signatures of cosmic rays and other energetic particles, such as those produced by radioactive decays. The algorithm, whose core component is a convolutional neural network, achieves classification performance comparable to human quality across four distinct DECO event topologies. We apply our model to the entire DECO data set and determine a selection that achieves $\ge90\%$ purity for all event types. In particular, we estimate a purity of $95\%$ when applied to cosmic-ray muons. The automated classification is run on the public DECO data set in real time in order to provide classified particle interaction images to users of the app and other interested members of the public., Comment: 14 pages, 14 figures, 1 table

The total area of silicon in cell phone camera sensors worldwide surpasses that in any experiment to date. Based on semiconductor technology similar to that found in modern astronomical telescopes and particle detectors, these sensors can detect ionizing radiation in addition to photons. The Distributed Electronic Cosmic-ray Observatory (DECO) uses the global network of active cell phones in order to detect cosmic rays and other energetic particles such as those produced by radioactive decays. DECO consists of an Android application, database, and public data browser available to citizen scientists around the world (https://wipac.wisc.edu/deco). Candidate cosmic-ray events have been detected on all seven continents and can be categorized by the morphology of their corresponding images. We present the DECO project, a novel particle detector with wide applications in public outreach and education., Comment: Presented at ICRC 2017, Busan, Korea. See https://wipac.wisc.edu/deco for more information

In 2014 the number of active cell phones worldwide for the first time surpassed the number of humans. Cell phone camera quality and onboard processing power (both CPU and GPU) continue to improve rapidly. In addition to their primary purpose of detecting photons, camera image sensors on cell phones and other ubiquitous devices such as tablets, laptops and digital cameras can detect ionizing radiation produced by cosmic rays and radioactive decays. While cosmic rays have long been understood and characterized as a nuisance in astronomical cameras, they can also be identified as a signal in idle camera image sensors. We present the Distributed Electronic Cosmic-ray Observatory (DECO), a platform for outreach and education as well as for citizen science. Consisting of an app and associated database and web site, DECO harnesses the power of distributed camera image sensors for cosmic-ray detection., Comment: presented at ICRC 2015, Den Haag, Netherlands