{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T18:05:36Z","timestamp":1776276336195,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":19,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T00:00:00Z","timestamp":1666310400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Innovation Project of GUET Graduate Education","award":["2022YCXS085"],"award-info":[{"award-number":["2022YCXS085"]}]},{"name":"Key Laboratory of Environmental Opatics and Technology, CAS","award":["No.2005DP173065-2018-04"],"award-info":[{"award-number":["No.2005DP173065-2018-04"]}]},{"name":"Science and Technology Major Project of Guangxi Zhuang Autonomous Region Government","award":["No.AA19046004"],"award-info":[{"award-number":["No.AA19046004"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,10,21]]},"DOI":"10.1145\/3569966.3569988","type":"proceedings-article","created":{"date-parts":[[2022,12,20]],"date-time":"2022-12-20T22:24:41Z","timestamp":1671575081000},"page":"75-79","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Algae Image Classification Algorithm Based on the Improved MobileNetV2"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4558-8771","authenticated-orcid":false,"given":"Ke","family":"Lin","sequence":"first","affiliation":[{"name":"School of Computer and Information Security, Guilin University of Electronic Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3597-0632","authenticated-orcid":false,"given":"Rusha","family":"Hao","sequence":"additional","affiliation":[{"name":"School of Computer and Information Security, Guilin University of Electronic Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4401-6285","authenticated-orcid":false,"given":"Shihao","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer and Information Security, Guilin University of Electronic Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3814-5777","authenticated-orcid":false,"given":"Jianheng","family":"Tang","sequence":"additional","affiliation":[{"name":"School of Computer and Information Security, Guilin University of Electronic Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2603-1983","authenticated-orcid":false,"given":"Zhisong","family":"Qin","sequence":"additional","affiliation":[{"name":"School of Computer and Information Security, Guilin University of Electronic Technology, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,12,20]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"The Application Study of Algae for Monitoring Water Quality[J]. Shandong Science","author":"Wang B L","year":"2007","unstructured":"Wang B L , Yang Y , Zhang L Q , The Application Study of Algae for Monitoring Water Quality[J]. Shandong Science , 2007 . Wang B L , Yang Y , Zhang L Q , The Application Study of Algae for Monitoring Water Quality[J]. Shandong Science, 2007."},{"key":"e_1_3_2_1_2_1","volume-title":"Advances in Pigment Analysis and Chemotaxonomy of Marine Phytoplankton[J]","author":"Deng C M","year":"2010","unstructured":"Deng C M , Yao P , Liu S X , Advances in Pigment Analysis and Chemotaxonomy of Marine Phytoplankton[J] . Periodical of Ocean University of China , 2010 . Deng C M , Yao P , Liu S X , Advances in Pigment Analysis and Chemotaxonomy of Marine Phytoplankton[J]. Periodical of Ocean University of China, 2010."},{"key":"e_1_3_2_1_3_1","volume-title":"Application of Molecular Biology to Microalgae Classification Research[J]","author":"Zhen Y","year":"2006","unstructured":"Zhen Y , Gang Y Z , Zhu M T . Application of Molecular Biology to Microalgae Classification Research[J] . Periodical of Ocean University of China , 2006 . Zhen Y , Gang Y Z , Zhu M T . Application of Molecular Biology to Microalgae Classification Research[J]. Periodical of Ocean University of China, 2006."},{"key":"e_1_3_2_1_4_1","volume-title":"Algorithm for Automatic Recognition of Red Tide Algal Images Captured by Flow Cytometry[J]. Computer Science","author":"Xie Z J","year":"2013","unstructured":"Xie Z J , Luo T W , Dai J W , Algorithm for Automatic Recognition of Red Tide Algal Images Captured by Flow Cytometry[J]. Computer Science , 2013 . Xie Z J , Luo T W, Dai J W , Algorithm for Automatic Recognition of Red Tide Algal Images Captured by Flow Cytometry[J]. Computer Science, 2013."},{"key":"e_1_3_2_1_5_1","volume-title":"Identification of microalgae species based on convolutional neural networks[J]","author":"Cui X S","year":"2021","unstructured":"Cui X S , Tian X Q , Kang W , Identification of microalgae species based on convolutional neural networks[J] . Journal of Shanghai Ocean University , 2021 . Cui X S, Tian X Q, Kang W, Identification of microalgae species based on convolutional neural networks[J]. Journal of Shanghai Ocean University, 2021."},{"key":"e_1_3_2_1_6_1","volume-title":"ImageNet Classification with Deep Convolutional Neural Networks[J]. Advances in neural information processing systems","author":"Krizhevsky A","year":"2012","unstructured":"Krizhevsky A , Sutskever I , Hinton G . ImageNet Classification with Deep Convolutional Neural Networks[J]. Advances in neural information processing systems , 2012 , 25(2). Krizhevsky A , Sutskever I , Hinton G . ImageNet Classification with Deep Convolutional Neural Networks[J]. Advances in neural information processing systems, 2012, 25(2)."},{"key":"e_1_3_2_1_7_1","volume-title":"A deep-learning VGG network model-based algorithm for marine single-celled algae identification[J]","author":"Wang Y Z","year":"2021","unstructured":"Wang Y Z , Cheng Y , Bi H , A deep-learning VGG network model-based algorithm for marine single-celled algae identification[J] . Journal of Dalian Ocean University , 2021 . Wang Y Z, Cheng Y, Bi H, A deep-learning VGG network model-based algorithm for marine single-celled algae identification[J]. Journal of Dalian Ocean University, 2021."},{"key":"e_1_3_2_1_8_1","volume-title":"Computer Science","author":"Simonyan K","year":"2014","unstructured":"Simonyan K , Zisserman A . Very Deep Convolutional Networks for Large-Scale Image Recognition[J] . Computer Science , 2014 . Simonyan K , Zisserman A . Very Deep Convolutional Networks for Large-Scale Image Recognition[J]. Computer Science, 2014."},{"key":"e_1_3_2_1_9_1","volume-title":"SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and < 0.5MB model size[J]","author":"Iandola F N","year":"2016","unstructured":"Iandola F N , Han S , Moskewicz M W , SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and < 0.5MB model size[J] . 2016 . Iandola F N , Han S , Moskewicz M W , SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and < 0.5MB model size[J]. 2016."},{"key":"e_1_3_2_1_10_1","volume-title":"ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices[J]","author":"Zhang X","year":"2017","unstructured":"Zhang X , Zhou X , Lin M , ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices[J] . 2017 . Zhang X , Zhou X , Lin M , ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices[J]. 2017."},{"key":"e_1_3_2_1_11_1","volume-title":"Xception: Deep Learning with Depthwise Separable Convolutions[J]","author":"Chollet F .","year":"2017","unstructured":"Chollet F . Xception: Deep Learning with Depthwise Separable Convolutions[J] . IEEE , 2017 . Chollet F . Xception: Deep Learning with Depthwise Separable Convolutions[J]. IEEE, 2017."},{"key":"e_1_3_2_1_12_1","volume-title":"MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications[J]","author":"Howard A G","year":"2017","unstructured":"Howard A G , Zhu M , Chen B , MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications[J] . 2017 . Howard A G , Zhu M , Chen B , MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications[J]. 2017."},{"key":"e_1_3_2_1_13_1","volume-title":"IEEE","author":"Sandler M","year":"2018","unstructured":"Sandler M , Howard A , Zhu M , MobileNet V2 : Inverted Residuals and Linear Bottlenecks[C]\/\/ 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . IEEE , 2018 . Sandler M , Howard A , Zhu M , MobileNetV2: Inverted Residuals and Linear Bottlenecks[C]\/\/ 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2018."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_1_15_1","volume-title":"Squeeze-and-Excitation Networks[J]","author":"Jie H","year":"2017","unstructured":"Jie H , Li S , Gang S , Squeeze-and-Excitation Networks[J] . IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017 , PP( 99). Jie H , Li S , Gang S , Squeeze-and-Excitation Networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017, PP(99)."},{"key":"e_1_3_2_1_16_1","first-page":"3","volume":"2018","unstructured":"WOO S, PARK J, LEE J Y, Cbam:convolutional block attention module[C]\/\/Proceedings of the European Conference on Computer Vision)ECCV( , 2018 : 3 - 19 . WOO S, PARK J, LEE J Y, et al.Cbam:convolutional block attention module[C]\/\/Proceedings of the European Conference on Computer Vision)ECCV(, 2018:3-19.","journal-title":"Cbam:convolutional block attention module[C]\/\/Proceedings of the European Conference on Computer Vision)ECCV("},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01350"},{"key":"e_1_3_2_1_18_1","volume-title":"A ConvNet for the 2020s[J]. arXiv e-prints","author":"Liu Z","year":"2022","unstructured":"Liu Z , Mao H , Wu C Y , A ConvNet for the 2020s[J]. arXiv e-prints , 2022 . Liu Z , Mao H , Wu C Y , A ConvNet for the 2020s[J]. arXiv e-prints, 2022."},{"key":"e_1_3_2_1_19_1","volume-title":"Automated Diatom Classification (Part A):Handcrafted feature approaches. Appl. Sci","author":"Bueno G","year":"2017","unstructured":"Bueno G , Deniz O , Pedraza A , Automated Diatom Classification (Part A):Handcrafted feature approaches. Appl. Sci . 2017 . Bueno G , Deniz O , Pedraza A , Automated Diatom Classification (Part A):Handcrafted feature approaches. Appl. Sci. 2017."}],"event":{"name":"CSSE 2022: 2022 5th International Conference on Computer Science and Software Engineering","location":"Guilin China","acronym":"CSSE 2022"},"container-title":["Proceedings of the 5th International Conference on Computer Science and Software Engineering"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3569966.3569988","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3569966.3569988","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:49:19Z","timestamp":1750182559000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3569966.3569988"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,21]]},"references-count":19,"alternative-id":["10.1145\/3569966.3569988","10.1145\/3569966"],"URL":"https:\/\/doi.org\/10.1145\/3569966.3569988","relation":{},"subject":[],"published":{"date-parts":[[2022,10,21]]},"assertion":[{"value":"2022-12-20","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}