{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T00:06:11Z","timestamp":1768435571936,"version":"3.49.0"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030210762","type":"print"},{"value":"9783030210779","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-21077-9_14","type":"book-chapter","created":{"date-parts":[[2019,6,18]],"date-time":"2019-06-18T23:14:41Z","timestamp":1560899681000},"page":"149-158","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Rock Detection in a Mars-Like Environment Using a CNN"],"prefix":"10.1007","author":[{"given":"Federico","family":"Furl\u00e1n","sequence":"first","affiliation":[]},{"given":"Elsa","family":"Rubio","sequence":"additional","affiliation":[]},{"given":"Humberto","family":"Sossa","sequence":"additional","affiliation":[]},{"given":"V\u00edctor","family":"Ponce","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,5,18]]},"reference":[{"key":"14_CR1","doi-asserted-by":"publisher","unstructured":"Castano, R., et al.: Onboard autonomous rover science. In: 2007 IEEE Aerospace Conference, pp. 1\u201313, March 2007. https:\/\/doi.org\/10.1109\/AERO.2007.352700","DOI":"10.1109\/AERO.2007.352700"},{"key":"14_CR2","doi-asserted-by":"publisher","unstructured":"Castano, R., et al.: Current results from a rover science data analysis system. In: 2005 IEEE Aerospace Conference, pp. 356\u2013365, March 2005. https:\/\/doi.org\/10.1109\/AERO.2005.1559328","DOI":"10.1109\/AERO.2005.1559328"},{"key":"14_CR3","doi-asserted-by":"crossref","unstructured":"Chollet, F.: Xception: Deep learning with depthwise separable convolutions. CoRR (2016)","DOI":"10.1109\/CVPR.2017.195"},{"issue":"2","key":"14_CR4","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1016\/j.robot.2013.11.003","volume":"62","author":"Y Gao","year":"2014","unstructured":"Gao, Y., Spiteri, C., Pham, M.T., Al-Milli, S.: A survey on recent object detection techniques useful for monocular vision-based planetary terrain classification. Robot. Auton. Syst. 62(2), 151\u2013167 (2014)","journal-title":"Robot. Auton. Syst."},{"key":"14_CR5","doi-asserted-by":"crossref","unstructured":"Gong, X., Liu, J.: Rock detection via superpixel graph cuts. In: 19th IEEE International Conference on Image Processing (2012)","DOI":"10.1109\/ICIP.2012.6467318"},{"key":"14_CR6","volume-title":"Deep Learning","author":"I Goodfellow","year":"2016","unstructured":"Goodfellow, I., Bengio, Y., Courville, A.: Deep Learning. MIT Press, Cambridge (2016)"},{"key":"14_CR7","doi-asserted-by":"publisher","unstructured":"Gor, V., Manduchi, R., Anderson, R., Mjolsness, E.: Autonomous rock detection for mars terrain. In: Space 2001 (AIAA), August 2001. https:\/\/doi.org\/10.2514\/6.2001-4597","DOI":"10.2514\/6.2001-4597"},{"key":"14_CR8","unstructured":"LeCun, Y.: Generalization and network design strategies. University of Toronto, Technical report (1989)"},{"key":"14_CR9","unstructured":"NASA: K10 robots: scouts for human explorers (2010). https:\/\/www.nasa.gov\/centers\/ames\/K10\/"},{"key":"14_CR10","unstructured":"Olson, J., Craig, D., National Aeronautics and Space Administration, Langley Research Center: NASA\u2019s Analog Missions: Paving the Way for Space Exploration. National Aeronautics and Space Administration (2011). https:\/\/books.google.com.mx\/books?id=-6hVnwEACAAJ"},{"key":"14_CR11","doi-asserted-by":"crossref","unstructured":"Rashno, A., Saraee, M., Sadri, S.: Mars image segmentation with most relevant features among wavelet and color features. In: AI & Robotics (IRANOPEN) (2015)","DOI":"10.1109\/RIOS.2015.7270747"},{"key":"14_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 234\u2013241. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28"},{"key":"14_CR13","unstructured":"Sasaki, Y.: The truth of the F-measure. School of Computer Science, University of Manchester, Technical report (2007)"},{"key":"14_CR14","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1016\/j.cviu.2012.12.002","volume":"117","author":"C Shang","year":"2013","unstructured":"Shang, C., Barnes, D.: Fuzzy-rough feature selection aided support vector machines for mars image classification. Comput. Vis. Image Underst. 117, 202\u2013213 (2013)","journal-title":"Comput. Vis. Image Underst."},{"key":"14_CR15","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1177\/0278364911433135","volume":"31","author":"P Furgale","year":"2012","unstructured":"Furgale, P., Carle, P., Enright, J., Barfoot, T.D.: The Devon Island rover navigation dataset. Int. J. Robot. Res. 31, 707\u2013713 (2012)","journal-title":"Int. J. Robot. Res."},{"key":"14_CR16","doi-asserted-by":"crossref","unstructured":"Thompson, D., Casta\u00f1o, R.: Performance comparison of rock detection algorithms for autonomous planetary geology. In: IEEE Aerospace Conference (2007)","DOI":"10.1109\/AERO.2007.352699"},{"key":"14_CR17","doi-asserted-by":"publisher","unstructured":"Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2001, vol. 1, pp. I, December 2001. https:\/\/doi.org\/10.1109\/CVPR.2001.990517","DOI":"10.1109\/CVPR.2001.990517"},{"key":"14_CR18","doi-asserted-by":"publisher","first-page":"626","DOI":"10.1016\/j.asr.2017.04.028","volume":"60","author":"X Xiao","year":"2017","unstructured":"Xiao, X., Cui, H., Yao, M., Tian, Y.: Autonomous rock detection on mars through region contrast. Adv. Space Res. 60, 626\u2013635 (2017)","journal-title":"Adv. Space Res."},{"key":"14_CR19","unstructured":"Zamora, E.: Minitaller-aprendizaje-profundo (2017). https:\/\/github.com\/ezamorag\/Minitaller-Aprendizaje-Profundo\/blob\/master\/codigos\/path_segmentation_training.ipynb"},{"key":"14_CR20","doi-asserted-by":"crossref","unstructured":"Zhao, H., Shi, J., Qi, X., Wang, X., Jia, J.: Pyramid scene parsing network. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017)","DOI":"10.1109\/CVPR.2017.660"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-21077-9_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,19]],"date-time":"2023-06-19T00:05:46Z","timestamp":1687133146000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-21077-9_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030210762","9783030210779"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-21077-9_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"18 May 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MCPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Mexican Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Quer\u00e9taro","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Mexico","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 June 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 June 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mcpr22019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.mcpr.org.mx","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"86","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"40","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"47% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.82","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.39","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}