Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Deep CNNs as a method to classify rotating objects based on monostatic RCS. Retrieved May 24, 2026, from https://4ort.xyz/entity/deep-cnns-as-a-method-to-classify-rotating-objects-based-on-monostatic-rcs
MLA“Deep CNNs as a method to classify rotating objects based on monostatic RCS.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/deep-cnns-as-a-method-to-classify-rotating-objects-based-on-monostatic-rcs.
BibTeX@misc{4ortxyz_deep-cnns-as-a-method-to-classify-rotating-objects-based-on-monostatic-rcs_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Deep CNNs as a method to classify rotating objects based on monostatic RCS}}, year = {2026}, url = {https://4ort.xyz/entity/deep-cnns-as-a-method-to-classify-rotating-objects-based-on-monostatic-rcs}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Deep CNNs as a method to classify rotating objects based on monostatic RCS — https://4ort.xyz/entity/deep-cnns-as-a-method-to-classify-rotating-objects-based-on-monostatic-rcs (retrieved 2026-05-24)
