{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:25:53Z","timestamp":1740122753095,"version":"3.37.3"},"reference-count":18,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2017,7,3]],"date-time":"2017-07-03T00:00:00Z","timestamp":1499040000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Initiative for High-Dimensional Data-Driven Science through Deepening of Sparse Modeling","award":["16H01542","26120515"],"award-info":[{"award-number":["16H01542","26120515"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Process Lett"],"published-print":{"date-parts":[[2018,6]]},"DOI":"10.1007\/s11063-017-9652-0","type":"journal-article","created":{"date-parts":[[2017,7,3]],"date-time":"2017-07-03T06:52:04Z","timestamp":1499064724000},"page":"767-782","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Support Vector Machine Histogram: New Analysis and Architecture Design Method of Deep Convolutional Neural Network"],"prefix":"10.1007","volume":"47","author":[{"given":"Satoshi","family":"Suzuki","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2412-0184","authenticated-orcid":false,"given":"Hayaru","family":"Shouno","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,7,3]]},"reference":[{"key":"9652_CR1","volume-title":"Pattern recognition and machine learning","author":"CM Bishop","year":"2006","unstructured":"Bishop CM (2006) Pattern recognition and machine learning. Springer, Berlin"},{"key":"9652_CR2","doi-asserted-by":"crossref","unstructured":"Deng J, Dong W, Socher R, Li LJ, Li K, Fei-Fei L (2009) ImageNet: a large-scale hierarchical image database. In: CVPR09","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"9652_CR3","doi-asserted-by":"crossref","unstructured":"Deng L, Yu D (2014) Deep learning: Methods and applications. Tech. Rep. MSR-TR-2014-21, Microsoft Research. http:\/\/research.microsoft.com\/apps\/pubs\/default.aspx?id=209355","DOI":"10.1561\/2000000039"},{"key":"9652_CR4","unstructured":"Donahue J, Jia Y, Vinyals O, Hoffman J, Zhang N, Tzeng E, Darrell T (2013) Decaf: a deep convolutional activation feature for generic visual recognition. CoRR arXiv:1310.1531"},{"issue":"4","key":"9652_CR5","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1007\/BF00344251","volume":"36","author":"K Fukushima","year":"1980","unstructured":"Fukushima K (1980) Neocognitron: a self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position. Biol Cybern 36(4):193\u2013202","journal-title":"Biol Cybern"},{"key":"9652_CR6","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1016\/j.neunet.2012.09.016","volume":"37","author":"K Fukushima","year":"2013","unstructured":"Fukushima K (2013) Artificial vision by multi-layered neural networks: neocognitron and its advances. Neural Netw 37:103\u2013119. doi: 10.1016\/j.neunet.2012.09.016","journal-title":"Neural Netw"},{"key":"9652_CR7","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: IEEE conference on computer vision and pattern recognition (CVPR), pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"key":"9652_CR8","doi-asserted-by":"crossref","unstructured":"Jia Y, Shelhamer E, Donahue J, Karayev S, Long J, Girshick RB, Guadarrama S, Darrell T (2014) Caffe: convolutional architecture for fast feature embedding. CoRR arXiv:1408.5093","DOI":"10.1145\/2647868.2654889"},{"key":"9652_CR9","unstructured":"Krizhevsky A (2009) Learning multiple layers of features from tiny images. Tech. rep., Department of Computer Science, University of Toronto"},{"key":"9652_CR10","unstructured":"Krizhevsky A, Nair V, Hinton GE (2009) Cifar-10 and cifar-100 datasets. http:\/\/www.cs.toronto.edu\/~kriz\/cifar.html . Accessed 18 Jan 2017"},{"key":"9652_CR11","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks. In: Advances in neural information processing systems 25, Curran Associates, Inc., pp 1097\u20131105. http:\/\/papers.nips.cc\/paper\/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf"},{"issue":"4","key":"9652_CR12","doi-asserted-by":"crossref","first-page":"541","DOI":"10.1162\/neco.1989.1.4.541","volume":"1","author":"Y LeCun","year":"1989","unstructured":"LeCun Y, Boser B, Denker JS, Henderson D, Howard RE, Hubbard W, Jackel L (1989) Backpropagation applied to handwritten zip code recognition. Neural Comput 1(4):541\u2013551","journal-title":"Neural Comput"},{"key":"9652_CR13","unstructured":"Lin M, Chen Q, Yan S (2013) Network in network. CoRR arXiv:1312.4400"},{"key":"9652_CR14","unstructured":"Shouno H (2007) Recent studies around the neocognitron. In: Neural information processing, 14th international conference, ICONIP 2007, Kitakyushu, Japan, November 13\u201316, 2007, Revised Selected Papers, Part I, Springer, lecture notes in computer science, vol 4984, pp 1061\u20131070"},{"key":"9652_CR15","doi-asserted-by":"crossref","unstructured":"Shouno H, Suzuki S, Kido S (2015) A transfer learning method with deep convolutional neural network for diffuse lung disease classification. In: Neural information processing, 22nd international conference, ICONIP 2015, Istanbul, Turkey, November 9\u201312, 2015, Proceedings, Part I, Springer, lecture notes in computer science, vol 9489, pp 199\u2013207","DOI":"10.1007\/978-3-319-26532-2_22"},{"key":"9652_CR16","doi-asserted-by":"crossref","unstructured":"Silver D, Huang A, Maddison CJ, Guez A, Sifre L, Driessche GVD, Schrittwieser J, Antonoglou I, Panneershelvam V, Lanctot M, Dieleman S, Grewe D, Nham J, Kalchbrenner N, Sutskever I, Lillicrap T, Leach M, Kavukcuoglu K, Graepel T, Hassabis D (2016) Mastering the game of go with deep neural networks and tree search. Nature 529:484\u2013503, http:\/\/www.nature.com\/nature\/journal\/v529\/n7587\/full\/nature16961.html","DOI":"10.1038\/nature16961"},{"key":"9652_CR17","unstructured":"Simonyan K, Vedaldi A, Zisserman A (2014) Deep inside convolutional networks: visualising image classification models and saliency maps. In: International conference on learning representations workshop"},{"key":"9652_CR18","doi-asserted-by":"publisher","unstructured":"Zeiler MD, Fergus R (2014) Visualizing and understanding convolutional networks. In: Computer vision - ECCV 2014 - 13th European conference, Zurich, Switzerland, September 6\u201312, 2014, Proceedings, Part I, pp 818\u2013833. doi: 10.1007\/978-3-319-10590-1_53","DOI":"10.1007\/978-3-319-10590-1_53"}],"container-title":["Neural Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11063-017-9652-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-017-9652-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11063-017-9652-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,28]],"date-time":"2019-09-28T02:50:12Z","timestamp":1569639012000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11063-017-9652-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,7,3]]},"references-count":18,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2018,6]]}},"alternative-id":["9652"],"URL":"https:\/\/doi.org\/10.1007\/s11063-017-9652-0","relation":{},"ISSN":["1370-4621","1573-773X"],"issn-type":[{"type":"print","value":"1370-4621"},{"type":"electronic","value":"1573-773X"}],"subject":[],"published":{"date-parts":[[2017,7,3]]}}}