491 to 500 of 1,026 Results
Dec 14, 2023 -
Replication Data for: Smart Scissor: Coupling Spatial Redundancy Reduction and CNN Compression for Embedded Hardware
Unknown - 485 B -
MD5: 6cfe91619d41bdc5298289ae0e5e33d2
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Dec 14, 2023 -
Replication Data for: Smart Scissor: Coupling Spatial Redundancy Reduction and CNN Compression for Embedded Hardware
Unknown - 365 B -
MD5: 9e9e2ce18985f821ae98999cfdae6a87
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Dec 14, 2023 -
Replication Data for: Smart Scissor: Coupling Spatial Redundancy Reduction and CNN Compression for Embedded Hardware
Unknown - 455 B -
MD5: c901f7a84c207759c3db593dcb6890d5
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Dec 14, 2023 -
Replication Data for: Smart Scissor: Coupling Spatial Redundancy Reduction and CNN Compression for Embedded Hardware
Unknown - 449 B -
MD5: 76f8e5b75607222a145bfe468b0fc476
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Dec 14, 2023 -
Replication Data for: Smart Scissor: Coupling Spatial Redundancy Reduction and CNN Compression for Embedded Hardware
Python Source Code - 8.4 KB -
MD5: 92f7a5286ee892e5468c20864fcedab2
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Dec 14, 2023 -
Replication Data for: Smart Scissor: Coupling Spatial Redundancy Reduction and CNN Compression for Embedded Hardware
Python Source Code - 988 B -
MD5: 52f6a09702e9f9e3447b7af745472e40
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Dec 14, 2023 -
Replication Data for: Smart Scissor: Coupling Spatial Redundancy Reduction and CNN Compression for Embedded Hardware
Python Source Code - 2.5 KB -
MD5: e408b7c249eef6df70e6d7b27c333260
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Dec 14, 2023 -
Replication Data for: Smart Scissor: Coupling Spatial Redundancy Reduction and CNN Compression for Embedded Hardware
Python Source Code - 4.7 KB -
MD5: 47e70bb8eb5a7c3259c86520ff7e19d0
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Dec 14, 2023 -
Replication Data for: Smart Scissor: Coupling Spatial Redundancy Reduction and CNN Compression for Embedded Hardware
Unknown - 479 B -
MD5: 89774fdc005a7aedb55eebde5fefc1e2
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Dec 14, 2023 - Kong Hao
Kong, Hao; Liu, Weichen, 2023, "Replication Data for: EMNAPE: Efficient Multi-Dimensional Neural Architecture Pruning for EdgeAI", https://doi.org/10.21979/N9/HGFYTJ, DR-NTU (Data), V1, UNF:6:YowCvL3Bn3yfomoWb2+WPg== [fileUNF]
This dataset is created to restore the related data of the following published paper: Hao Kong, Xiangzhong Luo, Shuo Huai, Di Liu, Ravi Subramaniam, Christian Makaya, Qian Lin, Weichen Liu*, “EMNAPE: Efficient Multi-Dimensional Neural Architecture Pruning for EdgeAI”, ACM/IEEE De... |
