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321 to 330 of 454 Results
train_tuner-1.yaml
Dec 14, 2023 - Replication Data for: Smart Scissor: Coupling Spatial Redundancy Reduction and CNN Compression for Embedded Hardware
Unknown - 449 B - MD5: 76f8e5b75607222a145bfe468b0fc476
transforms-1.py
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
utils-1.py
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
utils-1.py
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
vgg-1.py
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
vgg_cifar-1.yaml
Dec 14, 2023 - Replication Data for: Smart Scissor: Coupling Spatial Redundancy Reduction and CNN Compression for Embedded Hardware
Unknown - 479 B - MD5: 89774fdc005a7aedb55eebde5fefc1e2
augment.py
Dec 14, 2023 - Replication Data for: EMNAPE: Efficient Multi-Dimensional Neural Architecture Pruning for EdgeAI
Python Source Code - 7.1 KB - MD5: d1ff82dff8c0e033758fd4c7686d1b31
benchmark.py
Dec 14, 2023 - Replication Data for: EMNAPE: Efficient Multi-Dimensional Neural Architecture Pruning for EdgeAI
Python Source Code - 7.4 KB - MD5: 43d7422a7337851ad25eb31b284e3ea9
benchmark_resnet50.csv
Dec 14, 2023 - Replication Data for: EMNAPE: Efficient Multi-Dimensional Neural Architecture Pruning for EdgeAI
Comma Separated Values - 485 B - MD5: b9c3f333d8f062b4e9544d0ef204e2fd
benchmark_resnet50.yaml
Dec 14, 2023 - Replication Data for: EMNAPE: Efficient Multi-Dimensional Neural Architecture Pruning for EdgeAI
Unknown - 288 B - MD5: 39416d452f5b4dd008c7f8d1b8a52150
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