Matches in SemOpenAlex for { <https://semopenalex.org/work/W4320025942> ?p ?o ?g. }
Showing items 1 to 87 of
87
with 100 items per page.
- W4320025942 abstract "The classification of marine moving targets is an important research topic. There are many methods to apply deep learning to target classification, such as convolution neural networks (CNNs). However, CNNs have complex network structures and large numbers of parameters, and cannot pay attention to the spatial information of the target. This paper proposes a new method for the classification of marine moving targets based on an adaptive multi-feature extraction module and a capsule network (DA_CapsNet). The attention mechanism captures the dependencies between feature channels and enhances the weights of salient features. Different from the Squeeze-and-Excitation network (SENet), SENet_avgmax can weight the feature maps comprehensively. Experimental results show that the proposed method achieves better classification performance compared to the state-of-the-art methods." @default.
- W4320025942 created "2023-02-12" @default.
- W4320025942 creator A5012122077 @default.
- W4320025942 creator A5054620276 @default.
- W4320025942 creator A5076270465 @default.
- W4320025942 date "2022-12-16" @default.
- W4320025942 modified "2023-09-26" @default.
- W4320025942 title "Marine Moving Target Classification Based on Capsule Network with Feature Enhancement" @default.
- W4320025942 cites W2903926094 @default.
- W4320025942 cites W2914315257 @default.
- W4320025942 cites W2937279530 @default.
- W4320025942 cites W2963420686 @default.
- W4320025942 cites W2979450738 @default.
- W4320025942 cites W2981513182 @default.
- W4320025942 cites W2990593259 @default.
- W4320025942 cites W3000097815 @default.
- W4320025942 cites W3001136015 @default.
- W4320025942 cites W3007352029 @default.
- W4320025942 cites W3010857163 @default.
- W4320025942 cites W3022798719 @default.
- W4320025942 cites W3032972472 @default.
- W4320025942 cites W3039028697 @default.
- W4320025942 cites W3041229178 @default.
- W4320025942 cites W3043388524 @default.
- W4320025942 cites W3080782931 @default.
- W4320025942 cites W3093815437 @default.
- W4320025942 cites W3100174574 @default.
- W4320025942 cites W3123494320 @default.
- W4320025942 cites W3127969803 @default.
- W4320025942 cites W3127996390 @default.
- W4320025942 cites W3128009745 @default.
- W4320025942 cites W3128328063 @default.
- W4320025942 cites W3128842017 @default.
- W4320025942 cites W3131423289 @default.
- W4320025942 cites W3155699321 @default.
- W4320025942 cites W3166348865 @default.
- W4320025942 cites W3187736118 @default.
- W4320025942 cites W3196948083 @default.
- W4320025942 cites W3198106997 @default.
- W4320025942 cites W3198386254 @default.
- W4320025942 doi "https://doi.org/10.1109/iciea54703.2022.10006181" @default.
- W4320025942 hasPublicationYear "2022" @default.
- W4320025942 type Work @default.
- W4320025942 citedByCount "0" @default.
- W4320025942 crossrefType "proceedings-article" @default.
- W4320025942 hasAuthorship W4320025942A5012122077 @default.
- W4320025942 hasAuthorship W4320025942A5054620276 @default.
- W4320025942 hasAuthorship W4320025942A5076270465 @default.
- W4320025942 hasConcept C138885662 @default.
- W4320025942 hasConcept C153180895 @default.
- W4320025942 hasConcept C154945302 @default.
- W4320025942 hasConcept C2776401178 @default.
- W4320025942 hasConcept C2780719617 @default.
- W4320025942 hasConcept C41008148 @default.
- W4320025942 hasConcept C41895202 @default.
- W4320025942 hasConcept C45347329 @default.
- W4320025942 hasConcept C50644808 @default.
- W4320025942 hasConcept C52622490 @default.
- W4320025942 hasConcept C81363708 @default.
- W4320025942 hasConceptScore W4320025942C138885662 @default.
- W4320025942 hasConceptScore W4320025942C153180895 @default.
- W4320025942 hasConceptScore W4320025942C154945302 @default.
- W4320025942 hasConceptScore W4320025942C2776401178 @default.
- W4320025942 hasConceptScore W4320025942C2780719617 @default.
- W4320025942 hasConceptScore W4320025942C41008148 @default.
- W4320025942 hasConceptScore W4320025942C41895202 @default.
- W4320025942 hasConceptScore W4320025942C45347329 @default.
- W4320025942 hasConceptScore W4320025942C50644808 @default.
- W4320025942 hasConceptScore W4320025942C52622490 @default.
- W4320025942 hasConceptScore W4320025942C81363708 @default.
- W4320025942 hasFunder F4320310931 @default.
- W4320025942 hasLocation W43200259421 @default.
- W4320025942 hasOpenAccess W4320025942 @default.
- W4320025942 hasPrimaryLocation W43200259421 @default.
- W4320025942 hasRelatedWork W1964120219 @default.
- W4320025942 hasRelatedWork W2144059113 @default.
- W4320025942 hasRelatedWork W2146076056 @default.
- W4320025942 hasRelatedWork W2295021132 @default.
- W4320025942 hasRelatedWork W2546942002 @default.
- W4320025942 hasRelatedWork W2767651786 @default.
- W4320025942 hasRelatedWork W2811390910 @default.
- W4320025942 hasRelatedWork W3003836766 @default.
- W4320025942 hasRelatedWork W4312376745 @default.
- W4320025942 hasRelatedWork W4312417841 @default.
- W4320025942 isParatext "false" @default.
- W4320025942 isRetracted "false" @default.
- W4320025942 workType "article" @default.