{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T11:34:00Z","timestamp":1773833640829,"version":"3.50.1"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2017,5,23]],"date-time":"2017-05-23T00:00:00Z","timestamp":1495497600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2018,4]]},"DOI":"10.1007\/s11042-017-4788-5","type":"journal-article","created":{"date-parts":[[2017,5,23]],"date-time":"2017-05-23T20:16:13Z","timestamp":1495570573000},"page":"9849-9869","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Deep learning based feature representation for automated skin histopathological image annotation"],"prefix":"10.1007","volume":"77","author":[{"given":"Gang","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Ching-Hsien Robert","family":"Hsu","sequence":"additional","affiliation":[]},{"given":"Huadong","family":"Lai","sequence":"additional","affiliation":[]},{"given":"Xianghan","family":"Zheng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,5,23]]},"reference":[{"issue":"22","key":"4788_CR1","doi-asserted-by":"crossref","first-page":"8007","DOI":"10.1088\/0031-9155\/58\/22\/8007","volume":"58","author":"R Ali","year":"2013","unstructured":"Ali R, Gunduz-Demir C, Szil\u00e1gyi T, Durkee B, Graves EE (2013) Semi-automatic segmentation of subcutaneous tumours from micro-computed tomography images. Phys Med Biol 58(22):8007","journal-title":"Phys Med Biol"},{"issue":"2011","key":"4788_CR2","first-page":"91","volume":"52","author":"CR Angel","year":"2011","unstructured":"Angel CR, Juan CC, Fabio AG (2011) Visual pattern mining in histology image collections using bag of features. Journal Artificial Intelligence in Medicine 52(2011):91\u2013106","journal-title":"Journal Artificial Intelligence in Medicine"},{"key":"4788_CR3","doi-asserted-by":"crossref","unstructured":"Baldi A, Murace R, Dragonetti E, Manganaro M, Bizzi S (2014) Automated content-based image retrieval: Application on dermoscopic images of pigmented skin lesions. In: Skin Cancer. Springer, pp 523\u2013528","DOI":"10.1007\/978-1-4614-7357-2_35"},{"issue":"1","key":"4788_CR4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/2200000006","volume":"2","author":"Y Bengio","year":"2009","unstructured":"Bengio Y (2009) Learning deep architectures for ai. Found Trends Mach Learn 2(1):1\u2013127","journal-title":"Found Trends Mach Learn"},{"key":"4788_CR5","doi-asserted-by":"crossref","unstructured":"Bengio Y (2013) Deep learning of representations: Looking forward. In: Proceedings of the 1st International Conference on Statistical Language and Speech Processing, Springer-Verlag, Berlin, Heidelberg, SLSP\u201913, pp 1\u201337","DOI":"10.1007\/978-3-642-39593-2_1"},{"key":"4788_CR6","volume-title":"Pattern recognition and machine learning (information science and statistics)","author":"CM Bishop","year":"2006","unstructured":"Bishop CM (2006) Pattern recognition and machine learning (information science and statistics). Springer-Verlag, Secaucus"},{"issue":"9","key":"4788_CR7","doi-asserted-by":"crossref","first-page":"1892","DOI":"10.1016\/j.patcog.2010.10.024","volume":"44","author":"K Bunte","year":"2011","unstructured":"Bunte K, Biehl M, Jonkman MF, Petkov N (2011) Learning effective color features for content based image retrieval in dermatology. Pattern Recogn 44(9):1892\u20131902","journal-title":"Pattern Recogn"},{"key":"4788_CR8","doi-asserted-by":"crossref","unstructured":"Caicedo JC, Cruz-Roa A, Gonz\u00e1lez FA (2009) Histopathology image classification using bag of features and kernel functions. In: Combi C, Shahar Y, Abu-Hanna A (eds) Proceedings of AIME, Lecture Notes in Computer Science, vol 5651, pp 126\u2013135","DOI":"10.1007\/978-3-642-02976-9_17"},{"issue":"4","key":"4788_CR9","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1016\/j.jaad.2009.09.009","volume":"63","author":"L Cerroni","year":"2010","unstructured":"Cerroni L, Argenyi Z, Cerio R, Facchetti F, Kittler H, Kutzner H, Requena L, Sangueza OP, Smoller B, Wechsler J, Kerl H (2010) Influence of evaluation of clinical pictures on the histopathologic diagnosis of inflammatory skin disorders. J Am Acad Dermatol 63(4):647\u201352","journal-title":"J Am Acad Dermatol"},{"key":"4788_CR10","doi-asserted-by":"crossref","unstructured":"Chen J, Zhao F, Cao H (2013) Knowledge acquisition from generalized experts oriented to product innovation. In: 2013 6th international conference on Information management, innovation management and industrial engineering (ICIII), vol 2. IEEE, pp 546\u2013549","DOI":"10.1109\/ICIII.2013.6703210"},{"key":"4788_CR11","first-page":"913","volume":"5","author":"Y Chen","year":"2004","unstructured":"Chen Y, Wang JZ (2004) Image categorization by learning and reasoning with regions. J Mach Learn Res 5:913\u2013939","journal-title":"J Mach Learn Res"},{"key":"4788_CR12","unstructured":"Cho Y (2012) Kernel methods for deep learning. PhD thesis, La Jolla, CA, USA, aAI3513249"},{"issue":"1-2","key":"4788_CR13","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/S0004-3702(96)00034-3","volume":"89","author":"TG Dietterich","year":"1997","unstructured":"Dietterich TG, Lathrop RH, Lozano-P\u00e9rez T (1997) Solving the multiple instance problem with axis-parallel rectangles. Artif Intell 89(1-2):31\u201371","journal-title":"Artif Intell"},{"key":"4788_CR14","doi-asserted-by":"crossref","unstructured":"Dong R (2011) Feature grouping technique to relax sample support requirement for sparse linear feature extraction. In: 2011 seventh international conference on Natural computation (ICNC), vol 3. IEEE, pp 1654\u20131657","DOI":"10.1109\/ICNC.2011.6022326"},{"issue":"4","key":"4788_CR15","doi-asserted-by":"crossref","first-page":"e5375","DOI":"10.1371\/journal.pone.0005375","volume":"4","author":"G Ferrara","year":"2009","unstructured":"Ferrara G, Argenyi Z, Argenziano G, Cerio R, Cerroni L, Di Blasi A, Feudale EA, Giorgio CM, Massone C, Nappi O, Tomasini C, Urso C, Zalaudek I, Kittler H, Soyer HP (2009) The influence of clinical information in the histopathologic diagnosis of melanocytic skin neoplasms. PLoS One 4(4):e5375","journal-title":"PLoS One"},{"issue":"1","key":"4788_CR16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1017\/S026988890999035X","volume":"25","author":"J Foulds","year":"2010","unstructured":"Foulds J, Frank E (2010) A review of multi-instance learning assumptions. Knowl Eng Rev 25(1):1\u201325","journal-title":"Knowl Eng Rev"},{"key":"4788_CR17","doi-asserted-by":"crossref","unstructured":"Gao L, Song J, Zou F, Zhang D, Shao J (2015) Scalable multimedia retrieval by deep learning hashing with relative similarity learning. In: Proceedings of the 23rd ACM International Conference on Multimedia, ACM, New York, NY, USA, MM \u201915, pp 903\u2013906","DOI":"10.1145\/2733373.2806360"},{"issue":"1-2","key":"4788_CR18","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/s10994-012-5283-x","volume":"88","author":"J He","year":"2012","unstructured":"He J, Gu H, Wang Z (2012) Bayesian multi-instance multi-label learning using gaussian process prior. Mach Learn 88(1-2):273\u2013295","journal-title":"Mach Learn"},{"issue":"5786","key":"4788_CR19","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1126\/science.1127647","volume":"313","author":"GE Hinton","year":"2006","unstructured":"Hinton GE, Salakhutdinov RR (2006) Reducing the dimensionality of data with neural networks. Science 313(5786):504\u2013507","journal-title":"Science"},{"issue":"7","key":"4788_CR20","doi-asserted-by":"crossref","first-page":"1527","DOI":"10.1162\/neco.2006.18.7.1527","volume":"18","author":"GE Hinton","year":"2006","unstructured":"Hinton GE, Osindero S, Teh YW (2006) A fast learning algorithm for deep belief nets. Neural Comput 18(7):1527\u201354","journal-title":"Neural Comput"},{"key":"4788_CR21","doi-asserted-by":"crossref","unstructured":"Huang PS, He X, Gao J, Deng L, Acero A, Heck L (2013) Learning deep structured semantic models for web search using clickthrough data. In: Proceedings of the 22nd ACM International Conference on Conference on Information & Knowledge Management, ACM, New York, NY, USA, CIKM \u201913, pp 2333\u20132338","DOI":"10.1145\/2505515.2505665"},{"issue":"6","key":"4788_CR22","first-page":"234:1","volume":"34","author":"Y Li","year":"2015","unstructured":"Li Y, Su H, Qi CR, Fish N, Cohen-Or D, Guibas LJ (2015) Joint embeddings of shapes and images via cnn image purification. ACM Trans Graph 34(6):234:1\u2013234:12","journal-title":"ACM Trans Graph"},{"issue":"1","key":"4788_CR23","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.patcog.2013.06.029","volume":"47","author":"N Lopes","year":"2014","unstructured":"Lopes N, Ribeiro B (2014) Towards adaptive learning with improved convergence of deep belief networks on graphics processing units. Pattern Recogn 47(1):114\u2013127","journal-title":"Pattern Recogn"},{"key":"4788_CR24","unstructured":"Malik MSA, Sulaiman S (2014) Dba\u2019s perspective on use of information visualization in electronic health records"},{"key":"4788_CR25","first-page":"012039","volume":"274","author":"AG Marrugo","year":"2011","unstructured":"Marrugo AG, Millan MS (2011) Retinal image analysis: preprocessing and feature extraction. Journal of Physics: Conference Series, IOP Publishing 274:012039","journal-title":"Journal of Physics: Conference Series, IOP Publishing"},{"key":"4788_CR26","doi-asserted-by":"crossref","unstructured":"Murthy VN, Maji S, Manmatha R (2015) Automatic image annotation using deep learning representations. In: Proceedings of the 5th ACM on International Conference on Multimedia Retrieval, ACM, New York, NY, USA, ICMR \u201915, pp 603\u2013606","DOI":"10.1145\/2671188.2749391"},{"key":"4788_CR27","doi-asserted-by":"crossref","unstructured":"Ooi BC, Tan KL, Wang S, Wang W, Cai Q, Chen G, Gao J, Luo Z, Tung AK, Wang Y, Xie Z, Zhang M, Zheng K (2015) Singa: A distributed deep learning platform. In: Proceedings of the 23rd ACM International Conference on Multimedia, ACM, New York, NY, USA, MM \u201915, pp 685\u2013688","DOI":"10.1145\/2733373.2807410"},{"issue":"2-3","key":"4788_CR28","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1023\/A:1007649029923","volume":"39","author":"RE Schapire","year":"2000","unstructured":"Schapire RE, Singer Y (2000) Boostexter: a boosting-based system for text categorization. Mach Learn 39(2-3):135\u2013168","journal-title":"Mach Learn"},{"issue":"8","key":"4788_CR29","doi-asserted-by":"crossref","first-page":"888","DOI":"10.1109\/34.868688","volume":"22","author":"J Shi","year":"2000","unstructured":"Shi J, Malik J (2000) NorMalized cuts and image segmentation. IEEE Trans Pattern Anal Mach Intell 22(8):888\u2013905","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"4788_CR30","doi-asserted-by":"crossref","unstructured":"Stoean C, Stoean R, Sandita A, Mesina C, Gruia CL, Ciobanu D (2015) Evolutionary search for an accurate contour segmentation in histopathological images. In: Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, ACM, New York, NY, USA, GECCO Companion \u201915, pp 1491\u20131492","DOI":"10.1145\/2739482.2764690"},{"key":"4788_CR31","unstructured":"Tang Y (2013) Deep learning using support vector machines. CoRR arXiv: 1306.0239"},{"key":"4788_CR32","first-page":"211","volume":"1","author":"ME Tipping","year":"2001","unstructured":"Tipping ME (2001) Sparse bayesian learning and the relevance vector machine. J Mach Learn Res 1:211\u2013244","journal-title":"J Mach Learn Res"},{"issue":"4","key":"4788_CR33","doi-asserted-by":"crossref","first-page":"49:1","DOI":"10.1145\/2685394","volume":"11","author":"HP Trinh","year":"2015","unstructured":"Trinh HP, Duranton M, Paindavoine M (2015) Efficient data encoding for convolutional neural network application. ACM Trans Archit Code Optim 11(4):49:1\u201349:21","journal-title":"ACM Trans Archit Code Optim"},{"key":"4788_CR34","unstructured":"Vincent P, Larochelle H, Lajoie I, Bengio Y, Manzagol PA (2010) Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion 11:3371\u20133408"},{"key":"4788_CR35","doi-asserted-by":"crossref","unstructured":"Zhang G, Shu X, Liang Z, Liang Y, Chen S, Yin J (2012a) Multi-instance learning for skin biopsy image features recognition, Philadelphia, PA, United states, pp 83\u201388","DOI":"10.1109\/BIBM.2012.6392648"},{"key":"4788_CR36","doi-asserted-by":"crossref","unstructured":"Zhang G, Yin J, Li Z, Liang Z, Fu W (2012b) Deep learning for acupuncture point selection patterns based on veteran doctor experience of chinese medicine. In: Proceedings of the 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW), IEEE Computer Society, Washington, DC, USA, BIBMW \u201912, pp 396\u2013401","DOI":"10.1109\/BIBMW.2012.6470346"},{"issue":"3","key":"4788_CR37","first-page":"1","volume":"6","author":"G Zhang","year":"2013","unstructured":"Zhang G, Yin J, Li Z, Su X, Li G, Zhang H (2013) Automated skin biopsy histopathological image annotation using multi-instance representation and learning. BMC Med Genet 6(3):1\u201314","journal-title":"BMC Med Genet"},{"key":"4788_CR38","doi-asserted-by":"crossref","unstructured":"Zhang G, Yin J, Su XY, Huang YJ, Lao YR, Liang ZH, Ou SX, Zhang HL (2014) Augmenting multi-instance multilabel learning with sparse bayesian models for skin biopsy image analysis. BioMed Research International 2014(Article ID 305629):13 pages","DOI":"10.1155\/2014\/305629"},{"key":"4788_CR39","doi-asserted-by":"crossref","unstructured":"Zhang ML (2009) Generalized multi-instance learning: Problems, algorithms and data sets","DOI":"10.1109\/GCIS.2009.7"},{"key":"4788_CR40","doi-asserted-by":"crossref","unstructured":"Zhang S, Huang Q, Hua G, Jiang S, Gao W, Tian Q (2010) Building contextual visual vocabulary for large-scale image applications. In: Proceedings of the international conference on Multimedia. ACM, pp 501\u2013510","DOI":"10.1145\/1873951.1874018"},{"key":"4788_CR41","doi-asserted-by":"crossref","unstructured":"Zhong R, Tezuka T (2014) Parametric learning of deep convolutional neural network. In: Proceedings of the 19th International Database Engineering & Applications Symposium, ACM, New York, NY, USA, IDEAS \u201915, pp 226\u2013227","DOI":"10.1145\/2790755.2790791"},{"issue":"1","key":"4788_CR42","doi-asserted-by":"crossref","first-page":"2291","DOI":"10.1016\/j.artint.2011.10.002","volume":"176","author":"ZH Zhou","year":"2012","unstructured":"Zhou ZH, Zhang ML, Huang SJ, Li YF (2012) Multi-instance multi-label learning. Artif Intell 176(1):2291\u20132320","journal-title":"Artif Intell"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11042-017-4788-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-017-4788-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-017-4788-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T19:26:46Z","timestamp":1750274806000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11042-017-4788-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,5,23]]},"references-count":42,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2018,4]]}},"alternative-id":["4788"],"URL":"https:\/\/doi.org\/10.1007\/s11042-017-4788-5","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,5,23]]}}}