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In order to solve the problem of sonar objective detection under the complex environment, a sonar objective detection method is proposed based on dilated separable densely connected convolutional neural networks (DS\u2010CNNs) and quantum\u2010behaved particle swarm optimization (QPSO) algorithm. Firstly, the dilated separable convolution kernel is proposed to extend the local receptive field and enhance the feature extraction ability of the convolution layers. Secondly, based on the linear interpolation algorithm, a multisampling pooling (MS\u2010pooling) operation is proposed to reduce the feature information loss and restore image resolution. At last, with contraction\u2010expansion factor and difference variance in the traditional particle swarm optimization algorithm introduced, the QPSO algorithm is employed to optimize the weight parameters of the network model. The proposed method is validated on the sonar image dataset and is compared with other existing methods. Using DS\u2010CNNs to detect different kinds of sonar objectives, the experiments shows that the detection accuracy of DS\u2010CNNs reaches 96.98% and DS\u2010CNNs have better detection effect and stronger robustness.<\/jats:p>","DOI":"10.1155\/2021\/6235319","type":"journal-article","created":{"date-parts":[[2021,1,19]],"date-time":"2021-01-19T19:35:09Z","timestamp":1611084909000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Sonar Objective Detection Based on Dilated Separable Densely Connected CNNs and Quantum\u2010Behaved PSO Algorithm"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5765-0827","authenticated-orcid":false,"given":"Zhen","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5097-2922","authenticated-orcid":false,"given":"Buhong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0490-7649","authenticated-orcid":false,"given":"Jianxin","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4534-5358","authenticated-orcid":false,"given":"Shanwen","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,1,19]]},"reference":[{"key":"e_1_2_9_1_2","first-page":"1","article-title":"A systematic review of the socioeconomic factors that influence how marine protected areas impact on ecosystems and livelihoods","volume":"7","author":"Mizrahi M.","year":"2018","journal-title":"Society & Natural Resources"},{"key":"e_1_2_9_2_2","unstructured":"PostolacheO. 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