Lintott, Chris J.

Galaxy Zoo: morphologies derived from visual inspection of galaxies from the Sloan Digital Sky Survey ★

Lintott, C. J., Schawinski, K., Slosar, A., Land, K., Bamford, S., Thomas, D., Raddick, M. J., Nichol, R. C., Szalay, A., Andreescu, D., et al. (2008) · Monthly Notices of the Royal Astronomical Society

Galaxies: Formation, Evolution, PhenomenaStellar, planetary, and galactic studies

Cited by 1,488

Galaxy Zoo 2: detailed morphological classifications for 304 122 galaxies from the Sloan Digital Sky Survey

Willett, K. W., Lintott, C. J., Bamford, S. P., Masters, K. L., Simmons, B. D., Casteels, K. R. V., Edmondson, E. M., Fortson, L. F., Kaviraj, S., Keel, W. C., et al. (2013) · Monthly Notices of the Royal Astronomical Society

Galaxies: Formation, Evolution, PhenomenaStellar, planetary, and galactic studies

Cited by 659

Snapshot Serengeti, high-frequency annotated camera trap images of 40 mammalian species in an African savanna

Swanson, A., Kosmala, M., Lintott, C., Simpson, R., Smith, A., & Packer, C. (2015) · Scientific Data

Wildlife Ecology and ConservationSpecies Distribution and Climate Change

Cited by 510

Planet Hunters IX. KIC 8462852 - Where's the Flux?

Boyajian, T. S., LaCourse, D. M., Rappaport, S. A., Fabrycky, D., Fischer, D. A., Gandolfi, D., Kennedy, G. M., Korhonen, H., Liu, M. C., Moor, A., et al. (2016) · Monthly Notices of the Royal Astronomical Society

Stellar, planetary, and galactic studiesAstronomy and Astrophysical Research

Cited by 291

Galaxy Zoo: probabilistic morphology through Bayesian CNNs and active learning

Walmsley, M., Smith, L., Lintott, C., Gal, Y., Bamford, S., Dickinson, H., Fortson, L., Kruk, S., Masters, K., Scarlata, C., et al. (2020) · Monthly Notices of the Royal Astronomical Society

Galaxies: Formation, Evolution, PhenomenaAdvanced Neural Network Applications

Cited by 160

Space Warps – I. Crowdsourcing the discovery of gravitational lenses

Marshall, P. J., Verma, A., More, A., Davis, C. P., More, S., Kapadia, A., Parrish, M., Snyder, C., Wilcox, J., Baeten, E., et al. (2016) · Monthly Notices of the Royal Astronomical Society

Astrophysical Phenomena and ObservationsGalaxies: Formation, Evolution, Phenomena

Cited by 117

Space Warps– II. New gravitational lens candidates from the CFHTLS discovered through citizen science

More, A., Verma, A., Marshall, P. J., More, S., Baeten, E., Wilcox, J., Macmillan, C., Cornen, C., Kapadia, A., Parrish, M., et al. (2016) · Monthly Notices of the Royal Astronomical Society

Galaxies: Formation, Evolution, PhenomenaAstrophysical Phenomena and Observations

Cited by 116

Survey of Gravitationally-lensed Objects in HSC Imaging (SuGOHI): VI. Crowdsourced lens finding with Space Warps

Sonnenfeld, A., Verma, A., More, A., Baeten, E., Macmillan, C., Wong, K. C., Chan, J. H. H., Jaelani, A. T., Lee, C.-H., Oguri, M., et al. (2020) · Astronomy & Astrophysics

Galaxies: Formation, Evolution, PhenomenaAstrophysical Phenomena and Observations

Cited by 67

Identification of low surface brightness tidal features in galaxies using convolutional neural networks

Walmsley, M., Ferguson, A. M. N., Mann, R. G., & Lintott, C. J. (2019) · Monthly Notices of the Royal Astronomical Society

Galaxies: Formation, Evolution, PhenomenaAdvanced Neural Network Applications

Cited by 66

Practical Galaxy Morphology Tools from Deep Supervised Representation Learning

Walmsley, M., Scaife, A. M. M., Lintott, C., Lochner, M., Etsebeth, V., Géron, T., Dickinson, H., Fortson, L., Kruk, S., Masters, K. L., et al. (2021) · arXiv

Galaxies: Formation, Evolution, PhenomenaAdvanced Neural Network Applications

Cited by 64

Zoobot: Adaptable Deep Learning Models for Galaxy Morphology

Walmsley, M., Allen, C., Aussel, B., Bowles, M., Gregorowicz, K., Slijepcevic, I. V., Lintott, C. J., Scaife, A. M. M., Jabłońska, M., Karchev, K., et al. (2023) · Journal of Open Source Software

Galaxies: Formation, Evolution, PhenomenaAdvanced Neural Network Applications

Cited by 45

Scaling Laws for Galaxy Images

Walmsley, M., Bowles, M., Scaife, A. M. M., Makechemu, J. S., Gordon, A. J., Ferguson, A. M. N., Mann, R. G., Pearson, J., Popp, J. J., Bovy, J., et al. (2024) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 2