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The detection models can get better results for big object. However, those models fail to detect small objects that have low resolution and are greatly influenced by noise because the features after repeated convolution operations of existing models do not fully represent the essential characteristics of the small objects. In this paper, we can achieve good detection accuracy by extracting the features at different convolution levels of the object and using the multiscale features to detect small objects. For our detection model, we extract the features of the image from their third, fourth, and 5th convolutions, respectively, and then these three scales features are concatenated into a one-dimensional vector. The vector is used to classify objects by classifiers and locate position information of objects by regression of bounding box. Through testing, the detection accuracy of our model for small objects is 11% higher than the state-of-the-art models. In addition, we also used the model to detect aircraft in remote sensing images and achieved good results.<\/jats:p>","DOI":"10.1155\/2018\/4546896","type":"journal-article","created":{"date-parts":[[2018,9,30]],"date-time":"2018-09-30T19:31:13Z","timestamp":1538335873000},"page":"1-10","source":"Crossref","is-referenced-by-count":51,"title":["Small Object Detection with Multiscale Features"],"prefix":"10.1155","volume":"2018","author":[{"given":"Guo X.","family":"Hu","sequence":"first","affiliation":[{"name":"College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China"},{"name":"School of Software, Jiangxi Normal University, Nanchang 330022, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7780-5646","authenticated-orcid":true,"given":"Zhong","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Computer Information Engineering, Jiangxi Normal University, Nanchang 330022, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Huang","sequence":"additional","affiliation":[{"name":"Elementary Education College, Jiangxi Normal University, Nanchang 330022, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jia M.","family":"Han","sequence":"additional","affiliation":[{"name":"College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","reference":[{"key":"6","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2577031"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2389824"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"},{"key":"28","doi-asserted-by":"publisher","DOI":"10.3390\/app8050813"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1109\/34.730558"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2014.2345401"},{"key":"12","series-title":"Lecture Notes in Computer Science","first-page":"214","volume-title":"R-CNN for small object detection","volume":"10115","year":"2016"},{"issue":"2","key":"13","first-page":"243","volume":"5","year":"2012","journal-title":"International Journal of Hybrid Information Technology"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.5120\/20084-2026"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1007\/s11265-015-1097-y"},{"key":"21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"22","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-013-0620-5"},{"key":"23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10602-1_26"},{"key":"25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"29","doi-asserted-by":"publisher","DOI":"10.23919\/TST.2017.8195348"}],"container-title":["International Journal of Digital Multimedia Broadcasting"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/ijdmb\/2018\/4546896.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/ijdmb\/2018\/4546896.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/ijdmb\/2018\/4546896.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2018,9,30]],"date-time":"2018-09-30T19:31:20Z","timestamp":1538335880000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/ijdmb\/2018\/4546896\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,9,30]]},"references-count":15,"alternative-id":["4546896","4546896"],"URL":"https:\/\/doi.org\/10.1155\/2018\/4546896","relation":{},"ISSN":["1687-7578","1687-7586"],"issn-type":[{"value":"1687-7578","type":"print"},{"value":"1687-7586","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,9,30]]}}}