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Performance evaluation of deep learning formats : a comparative study of ONNX and pytorch for inference efficiency and portability

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dc.contributor.authorMercado, Alfredo
dc.contributor.authorVillalobos, Johansell
dc.contributor.authorMeneses, Esteban
dc.date.accessioned2026-07-17T21:22:03Z
dc.date.available2026-07-17T21:22:03Z
dc.date.issued2026
dc.identifier.doidoi: 10.1109/BIP68491.2025.11489132
dc.identifier.urihttps://hdl.handle.net/20.500.12337/11793
dc.language.isoen_US
dc.publisher2025 IEEE 7th International Conference on BioInspired Processing (BIP).
dc.relationdoi: 10.1109/BIP68491.2025.11489132
dc.rightsacceso abierto
dc.source2025 IEEE 7th International Conference on BioInspired Processing (BIP), Pérez Zeledón, Costa Rica, 2025, pp. 1-6
dc.subjectAPRENDIZAJE PROFUNDO
dc.subjectCIENCIA Y TECNOLOGÍA
dc.titlePerformance evaluation of deep learning formats : a comparative study of ONNX and pytorch for inference efficiency and portability
dc.typeartículo de investigación

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