J/MNRAS/479/415ivo://CDS.VizieR/J/MNRAS/479/415doi:10.26093/cds/vizier.74790415CDSAckermann S.Schawinski K.Zhang C.Weigel A.K.Turp M.D.2024-08-18T20:20:46Z2022-07-07T13:26:20ZCDS support team

CDS, Observatoire de Strasbourg, 11 rue de l'Universite, F-67000 Strasbourg, France

cds-question@unistra.frgalaxiescatalogsWe investigate the use of deep convolutional neural networks (deep CNNs) for automatic visual detection of galaxy mergers. Moreover, we investigate the use of transfer learning in conjunction with CNNs by retraining networks first trained on pictures of everyday objects. We test the hypothesis that transfer learning is useful for improving classification performance for small training sets. This would make transfer learning useful for finding rare objects in astronomical imaging data sets. We find that these deep learning methods perform significantly better than current state-of-the-art merger detection methods based on non-parametric systems such as CAS and GM20. Our method is end-to-end and robust to image noise and distortions; it can be applied directly without image preprocessing. We also find that transfer learning can act as a regularizer in some cases, leading to better overall classification accuracy (p=0.02). Transfer learning on our full training set leads to a lowered error rate from 0.038+/-1 to 0.032+/-1, a relative improvement of 15 per cent. Finally, we perform a basic sanity-check by creating a merger sample with our method, and comparing with an already existing, manually created merger catalogue in terms of colour--mass distribution and stellar mass function.2018MNRAS.479..415Ahttps://cdsarc.cds.unistra.fr/viz-bin/cat/J/MNRAS/479/415CatalogResearchIsServedByTAP VizieR generic serviceIsServedByConesearch servicerelated-tohttp://zoo1.galaxyzoo.org : Galaxy Zoo Home Pagehttps://cds.unistra.fr/vizier-org/licences_vizier.htmlhttps://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/MNRAS/479/415https://vizier.iucaa.in/viz-bin/VizieR-2?-source=J/MNRAS/479/415http://vizieridia.saao.ac.za/viz-bin/VizieR-2?-source=J/MNRAS/479/415https://vizier.cds.unistra.fr/viz-bin/votable?-source=J/MNRAS/479/415https://vizier.iucaa.in/viz-bin/votable?-source=J/MNRAS/479/415http://vizieridia.saao.ac.za/viz-bin/votable?-source=J/MNRAS/479/415GETtext/xml+votablehttps://tapvizier.cds.unistra.fr/TAPVizieR/tapCone search capability for table J/MNRAS/479/415/table2 (Merger sample)https://vizier.cds.unistra.fr/viz-bin/conesearch/J/MNRAS/479/415/table2?https://vizier.iucaa.in/viz-bin/conesearch/J/MNRAS/479/415/table2?http://vizieridia.saao.ac.za/viz-bin/conesearch/J/MNRAS/479/415/table2?GETtext/xml+votable180.050000true171.533583327.910.0055555555555555561/5 8 10 27 2/16-17 19 25 28 38 103 107 3/72-73 75 97 116 144 146-147 176-178 184 407 409-411 423 427 494 4/297 299 399 468-469 472 580 582-583 600 602 624 716 718 724 740 744-746 1373 1375 1599 1621-1623 1625-1627 1685-1687 1691 1703 1707 1961-1963 1965-1967 1980 1982-1983 2027 5/136 138 1184-1185 1187 1193 1540-1541 1549 1585 1588-1589 1685 1728-1729 1732-1733 1880-1882 1896-1898 1900-1901 2325 2327 2368 2370 2376 2378 2504 2506 2515 2518 2521 2523-2524 2526 2528 2530 2536 2545 2547-2548 2550 2553 2555-2556 2868 2870 2876 2878 2968-2970 2988 3095 3097-3101 3136-3138 4223 4287 4303 4307-4310 4312-4314 4323 4325-4326 4328-4330 4351 4373-4375 4377-4380 4387-4390 4392-4394 4416 4437-4438 4441-4442 4444 4453-4455 4457-4458 4500-4502 4504-4506 4515-4518 4520-4522 4575 4596-4598 4601-4602 4629-4631 4633-4636 4645 4647 4651-4652 4654 4656 4672 4687 4693-4694 4697-4698 4709-4710 4713-4714 4736-4738 4751 4757-4758 4761-4762 4764 4773-4774 4777-4778 4831 4845-4847 4850-4854 4856 4917-4919 4921-4924 4933-4935 4937-4940 4944 4960 4995 4997-5002 5008 5461-5463 5469 5471 5491 5588-5589 5591 5597 5679 5761-5765 5768 5786 5797-5798 5801-5802 6391 6461-6463 6477-6479 6481-6483 6497-6499 6541-6543 6737-6739 6757-6759 6761-6763 6805-6807 6809-6811 6821-6823 6825-6827 7508-7510 7516 7823 7834 7841-7843 7856 7858-7859 7882-7883 7886 7924 7926 8102-8103 8105 8107 8114 8120 8122 8125 8127 9179 9181-9183 9191 9194-9196 9200-9202 11261-11263 12247 12253-12254 12271 12273-12276 12280 12282 6/0-2 4 521-524 526-527 538 548-550 556 640 4744-4745 4747 4769 4780-4781 4783 6149 6168-6169 6172-6173 6175 6205 6337 6363 6365-6367 6739 6976-6977 6980-6981 6992-6993 6996-6997 7532-7533 7536-7538 7568-7570 7572 7576 7579 7582-7583 7596-7597 7608-7609 7612 7680-7681 7684-7685 7696-7697 7700-7701 9306-9307 9486 9508 9510 9516 9518-9519 9530 9616 9618 9624-9626 9648 9650 9656 9658 10000 10020-10022 10028 10030 10067 10070 10116 10118 10124 10152-10154 10177 10179 10185 10187 10209 10211 10217 10219 10232-10234 11476-11478 11484 11486 11508 11520 11522 11528 11530 11552 11600 11602 11608 11610 11616-11617 11620-11621 11856 11858 11864 11884 11956 11960 11968-11970 12288-12290 12375 12377-12379 12387 12408-12410 12480-12481 12484 12556-12558 12560-12561 12563-12564 12568 12576 16887 16891 17207 17211 17223 17227 17244-17246 17260-17262 17264 17287 17297-17299 17308-17310 17324-17326 17328-17330 17344 17346 17469-17471 17485-17487 17490-17491 17505-17507 17524 17528 17547 17564-17566 17580-17582 17584-17586 17600-17602 17661-17663 17668-17670 17672-17673 17725-17727 17741-17743 17745-17747 17756-17758 17761-17763 17772-17774 17784 17805-17807 17809-17811 17825-17827 17836-17838 17840-17842 17856-17858 17920-17922 17981-17983 17997-17999 18012-18014 18028-18030 18032-18034 18076-18078 18092-18094 18096-18098 18104 18112-18114 18176-18178 18295 18299 18365-18367 18375 18381-18383 18396 18398 18401-18403 18412-18414 18416-18418 18495 18509-18511 18513-18515 18529-18531 18548 18552 18575 18579 18585-18587 18597-18599 18601-18603 18612-18614 18628 18632-18634 18683 18685-18687 18765-18767 18769-18771 18780-18782 18785-18787 18796-18798 18800-18802 18808 18829-18831 18833-18835 18844-18846 18849-18851 18860-18862 18864-18866 18880-18881 18883 18956 18958 18960 18976 18978 19021-19023 19025-19027 19036-19038 19041-19043 19052-19054 19085-19087 19089-19091 19100-19102 19105-19107 19116-19118 19120-19122 19136-19138 19144 19200-19202 19204 19319 19322-19323 19359 19371 19373-19375 19379 19397-19399 19420 19428-19430 19432-19434 19440 19456-19458 19583 19645-19647 19661-19663 19665-19667 19681-19683 19700 19704 19725-19727 19729 19731 19746-19747 19764 19768 19780 19784 19844 19848 19979 19985-19987 20012-20014 20016-20018 20036 20040 20096-20097 21843 21873 21883 21959 21963 21988 21991 21997 21999 22341 22360-22361 22363 22385 22396-22397 22399 22485 22487 22710-22711 22713-22715 22760 22762-22763 23043 23064-23066 23076-23077 23080 23101-23104 23138 23150 23179 23181-23183 23185-23187 23196-23198 23201-23203 23212-23214 23216-23218 23224 23232-23234 23236 25559 25579 25581-25583 25821-25823 25837-25839 25841-25843 25885-25887 25901-25903 25905-25907 25921-25923 25985-25987 26135 26139 26141-26143 26155 26157-26159 26161-26163 26877-26879 26903 26909-26911 26933 26941-26943 26945-26947 27021-27023 27025-27027 27041-27043 27197-27199 27213-27215 27217-27219 27233-27235 27277-27279 27281-27283 27297 27299 29973 30016 30029-30031 30044-30046 30068 31286 31289-31291 31330-31331 31340 31342 31353-31355 31357-31359 31363 31429-31431 31548 31550-31551 31594 31598-31599 31611 31710 32391 32397 32399 32402-32403 32406-32407 32425-32427 32460 32462 32478 32484 32486 32492 32494-32495 32497 32499 32505 32672 32674 32680 32682-32683 36607 36703 36715 36721-36723 36759 36761-36763 36771 36773-36775 36788-36790 36792-36794 36812 36814 36816-36818 36832 36861-36863 40957 40959 45023 45039 45043 48983 49005-49007 49009-49011 49020-49022 49077-49079 49081 49091 49108 49112 49114 49124-49125 49147 49149-49151https://cdsarc.cds.unistra.fr/viz-bin/moc/J/MNRAS/479/415?format=asciidefaultJ/MNRAS/479/415/table2Merger samplerecnoRecord number assigned by the VizieR team. Should Not be used for identification.meta.recordintobjIDSDSS objIDmeta.id;meta.mainRAJ2000Right ascension (J2000)pos.eq.ra;meta.mainindexedDEJ2000Declination (J2000)pos.eq.dec;meta.mainpmerger0[0/1]? Merger probability estimatestat.fit.goodnessdoublenullablepmerger1[0/1]? Merger probability estimatestat.fit.goodnessdoublenullablepmerger2[0/1]? Merger probability estimatestat.fit.goodnessdoublenullablepmerger3[0/1]? Merger probability estimatestat.fit.goodnessdoublenullableSloanDisplay the online SDSS data for the nearest objectmeta.ref.urlchar