GLF-Net: A Target Detection Method Based on Global and Local Multiscale Feature Fusion of Remote Sensing Aircraft Images
Summary
GLF-Net: A Target Detection Method Based on Global and Local Multiscale Feature Fusion of Remote Sensing Aircraft Images is a scholarly article[1].
Key Facts
GLF-Net: A Target Detection Method Based on Global and Local Multiscale Feature Fusion of Remote Sensing Aircraft Images's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). GLF-Net: A Target Detection Method Based on Global and Local Multiscale Feature Fusion of Remote Sensing Aircraft Images. Retrieved May 24, 2026, from https://4ort.xyz/entity/glf-net-a-target-detection-method-based-on-global-and-local-multiscale-feature-fusion-of-remote-sensing-aircraft-images
MLA“GLF-Net: A Target Detection Method Based on Global and Local Multiscale Feature Fusion of Remote Sensing Aircraft Images.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/glf-net-a-target-detection-method-based-on-global-and-local-multiscale-feature-fusion-of-remote-sensing-aircraft-images.
BibTeX@misc{4ortxyz_glf-net-a-target-detection-method-based-on-global-and-local-multiscale-feature-fusion-of-remote-sensing-aircraft-images_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{GLF-Net: A Target Detection Method Based on Global and Local Multiscale Feature Fusion of Remote Sensing Aircraft Images}}, year = {2026}, url = {https://4ort.xyz/entity/glf-net-a-target-detection-method-based-on-global-and-local-multiscale-feature-fusion-of-remote-sensing-aircraft-images}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): GLF-Net: A Target Detection Method Based on Global and Local Multiscale Feature Fusion of Remote Sensing Aircraft Images — https://4ort.xyz/entity/glf-net-a-target-detection-method-based-on-global-and-local-multiscale-feature-fusion-of-remote-sensing-aircraft-images (retrieved 2026-05-24)
