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In this study, we show that the inference accuracy can be improved by using an ensemble of a few BNNs. In addition, we report our implementation on an FPGA.","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Binarized Neural Network (BNN) is a promising technique for embedded inference hardware due to the small hardware cost, but the inference accuracy is degraded compared to a full-precision CNN. In this study, we show that the inference accuracy can be improved by using an ensemble of a few BNNs. In addition, we report our implementation on an FPGA.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告システム・アーキテクチャ（ARC）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2019-03-10","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"36","bibliographicVolumeNumber":"2019-ARC-235"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:00:07.884582+00:00","updated":"2025-01-19T23:12:45.007614+00:00"}