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Deep learning-based target identification algorithms currently do not fully leverage the link between high-level semantic and low-level detail information in the prediction step and hence are less successful in recognizing tiny target objects. Target recognition via vision sensors has also improved in accuracy and efficiency because of the development of deep learning. However, due to the insufficient usage of semantic information and precise texture information of underlying characteristics, tiny target recognition remains a difficulty. To address the aforementioned issues, we propose a target detection method based on a jump-connected pyramid model to improve the target detection performance of robots in complex scenarios. In order to verify the effectiveness of the algorithm, we designed and implemented a software system for target detection of intelligent robots and performed software integration of the proposed algorithm model with excellent experimental results. These experiments reveal that, when compared to other algorithms, our suggested algorithm\u2019s characteristics have higher flexibility and robustness and can deliver a higher scene classification accuracy rate.<\/jats:p>","DOI":"10.1155\/2022\/4037625","type":"journal-article","created":{"date-parts":[[2022,1,11]],"date-time":"2022-01-11T21:05:07Z","timestamp":1641935107000},"page":"1-14","source":"Crossref","is-referenced-by-count":2,"title":["A Deep Neural Network-Based Target Recognition Algorithm for Robot Scenes"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0799-9358","authenticated-orcid":true,"given":"Lijing","family":"Liu","sequence":"first","affiliation":[{"name":"School of Engineering, Hong Kong University of Science and Technology, Hong Kong 999077, China"}]}],"member":"311","reference":[{"doi-asserted-by":"publisher","key":"1","DOI":"10.1016\/j.wasman.2019.06.035"},{"doi-asserted-by":"publisher","key":"2","DOI":"10.1016\/j.compag.2020.105216"},{"doi-asserted-by":"publisher","key":"3","DOI":"10.3390\/ai1020008"},{"doi-asserted-by":"publisher","key":"4","DOI":"10.3389\/fpls.2020.00510"},{"key":"5","first-page":"569","article-title":"Private security robots, artificial intelligence, and deadly force","volume":"51","author":"E. 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