{"references": ["Pearson, K. A., Palafox, L., & Griffith, C. A. 2018, MNRAS, 474, 478, doi: 10.1093/mnras/stx2761", "Zucker, S., & Giryes, R. 2018, AJ, 155, 147, doi: 10.3847/1538-3881/aaae05", "Shallue, C. J., & Vanderburg, A. 2018, AJ, 155, 94, doi: 10.3847/1538-3881/aa9e09", "Ansdell, M., Ioannou, Y., Osborn, H. P., et al. 2018, ApJL, 869, L7, doi: 10.3847/2041-8213/aaf23b", "Dattilo, A., Vanderburg, A., Shallue, C. J., et al. 2019, AJ, 157, 169, doi: 10.3847/1538-3881/ab0e12", "Yu, L., Vanderburg, A., Huang, C., et al. 2019, AJ, 158, 25, doi: 10.3847/1538-3881/ab21d6", "Osborn, H. P., Ansdell, M., Ioannou, Y., et al. 2020, A&A, 633, A53, doi: 10.1051/0004-6361/201935345", "Schanche, N., Collier Cameron, A., H\u00e9brard, G., et al. 2019, MNRAS, 483, 5534, doi: 10.1093/mnras/sty3146", "Chaushev, A., Raynard, L., Goad, M. R., et al. 2019, MNRAS, 488, 5232, doi: 10.1093/mnras/stz2058", "Olmschenk, G., Ishitani Silva, S., Rau, G., et al. 2021, AJ, 161, 273, doi: 10.3847/1538-3881/abf4c6"]}

Deep learning algorithms are widely used in many fields of astronomy, and have a wide range of applications in transiting exoplanet detection and classification. We have trained an neural network using two-dimensional object detection algorithm with Kepler and TESS light curves. Our network outputs excellent performance on Kepler and TESS data. The detected transits can amplify their periodicity and our network can be easily used to find single transiting events and cluster multiple transits.