{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T18:08:13Z","timestamp":1764785293052,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":14,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819984121"},{"type":"electronic","value":"9789819984138"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-981-99-8413-8_3","type":"book-chapter","created":{"date-parts":[[2024,2,17]],"date-time":"2024-02-17T01:02:10Z","timestamp":1708131730000},"page":"45-64","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Accelerating Image Analysis Research with Active Learning Techniques in Genetic Programming"],"prefix":"10.1007","author":[{"given":"Nathan","family":"Haut","sequence":"first","affiliation":[]},{"given":"Wolfgang","family":"Banzhaf","sequence":"additional","affiliation":[]},{"given":"Bill","family":"Punch","sequence":"additional","affiliation":[]},{"given":"Dirk","family":"Colbry","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,2,18]]},"reference":[{"key":"3_CR1","doi-asserted-by":"publisher","first-page":"1071","DOI":"10.1016\/0893-6080(95)00137-9","volume":"9","author":"DA Cohn","year":"1996","unstructured":"Cohn, D.A.: Neural network exploration using optimal experiment design. Neural Netw. 9, 1071\u20131083 (1996)","journal-title":"Neural Netw."},{"issue":"1","key":"3_CR2","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1613\/jair.295","volume":"4","author":"DA Cohn","year":"1996","unstructured":"Cohn, D.A., Ghahramani, Z., Jordan, M.I.: Active learning with statistical models. J. Artif. Intell. Res. 4(1), 129\u2013145 (1996)","journal-title":"J. Artif. Intell. Res."},{"key":"3_CR3","unstructured":"Colbry, D.: See-Segment. https:\/\/github.com\/see-insight\/see-segment"},{"key":"3_CR4","doi-asserted-by":"crossref","unstructured":"Haut, N., Banzhaf, W., Punch, B.: Active learning improves performance on symbolic regression tasks in StackGP. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO \u201922, pp. 550\u2013553, New York, NY, USA. Association for Computing Machinery (2022)","DOI":"10.1145\/3520304.3528941"},{"key":"3_CR5","doi-asserted-by":"crossref","unstructured":"Kotanchek, M., Smits, G., Vladislavleva, E.: Exploiting trustable models via pareto gp for targeted data collection. In: Riolo, R., Soule, T., Worzel, B. eds., Genetic Programming Theory and Practice VI, pp. 145\u2013162. Springer (2009)","DOI":"10.1007\/978-0-387-87623-8_10"},{"key":"3_CR6","doi-asserted-by":"crossref","unstructured":"Kremer, J., Pedersen, K.S., Igel, C.: Active learning with support vector machines. WIREs Data Mining Knowl. Dis. 4(4), 313\u2013326 (2014)","DOI":"10.1002\/widm.1132"},{"key":"3_CR7","doi-asserted-by":"crossref","unstructured":"Lewis, D.D., Gale, W.A.: A sequential algorithm for training text classifiers. In: Bruce, W.C., van Rijsbergen, C.J. (eds.), SIGIR \u201994, London, pp. 3\u201312. Springer London (1994)","DOI":"10.1007\/978-1-4471-2099-5_1"},{"issue":"4","key":"3_CR8","doi-asserted-by":"publisher","first-page":"986","DOI":"10.1214\/aoms\/1177728069","volume":"27","author":"DV Lindley","year":"1956","unstructured":"Lindley, D.V.: On a measure of the information provided by an experiment. Ann. Math. Stat. 27(4), 986\u20131005 (1956)","journal-title":"Ann. Math. Stat."},{"issue":"9","key":"3_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3472291","volume":"54","author":"P Ren","year":"2021","unstructured":"Ren, P., Xiao, Y., Chang, X., Huang, P.-Y., Li, Z., Gupta, B.B., Chen, X., Wang, X.: A survey of deep active learning. ACM Comput. Surv. 54(9), 1\u201340 (2021)","journal-title":"ACM Comput. Surv."},{"key":"3_CR10","doi-asserted-by":"crossref","unstructured":"Ricker, B., Mitra, S., Castellanos, E.A., Grady, C.J., Pelled, G., Gilad, A.A.: Proposed three-phenylalanine motif involved in magnetoreception signaling of an actinopterygii protein expressed in mammalian cells (2022)","DOI":"10.1101\/2022.12.08.519643"},{"issue":"1","key":"3_CR11","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1146\/annurev-bioeng-071516-044442","volume":"19","author":"D Shen","year":"2017","unstructured":"Shen, D., Guorong, W., Suk, H.-I.: Deep learning in medical image analysis. Ann. Rev. Biomed. Eng. 19(1), 221\u2013248 (2017)","journal-title":"Ann. Rev. Biomed. Eng."},{"key":"3_CR12","doi-asserted-by":"crossref","unstructured":"Suk, H.-I., Shen, D.: Deep Learning in Diagnosis of Brain Disorders, pp. 203\u2013213. Springer Netherlands, Dordrecht (2015)","DOI":"10.1007\/978-94-017-7239-6_14"},{"key":"3_CR13","unstructured":"Uchiyama, H., Sakurai, S., Mishima, M., Arita, D., Okayasu, T., Shimada, A., Taniguchi, R.I.: KOMATSUNA Dataset"},{"issue":"2","key":"3_CR14","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1007\/s11831-016-9206-z","volume":"25","author":"J W\u00e4ldchen","year":"2018","unstructured":"W\u00e4ldchen, J., M\u00e4der, P.: Plant species identification using computer vision techniques: a systematic literature review. Arch. Comput. Methods Eng. 25(2), 507\u2013543 (2018)","journal-title":"Arch. Comput. Methods Eng."}],"container-title":["Genetic and Evolutionary Computation","Genetic Programming Theory and Practice XX"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-8413-8_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,11]],"date-time":"2024-11-11T18:41:29Z","timestamp":1731350489000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-8413-8_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819984121","9789819984138"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-8413-8_3","relation":{},"ISSN":["1932-0167","1932-0175"],"issn-type":[{"type":"print","value":"1932-0167"},{"type":"electronic","value":"1932-0175"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"18 February 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}