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01perturb-ai /efficientnet-v2-l-adv-dataset Perturb Adversarial Images Verified adversarial examples for efficientnet_v2_l (torchvision/EfficientNet_V2_L_Weights.IMAGENET1K_V1), produced by the Perturb network. Each row is one clean image together with all of its verified adversarial versions: images that are imperceptibly different from the original (L∞ ≤ 0.03 in [0,1] pixel scale) yet change the model's top-1 prediction. This dataset grows continuously. New rows are appended as the network produces them and uploaded in… See the full description on the dataset page: https://huggingface.co/datasets/perturb-ai/efficientnet-v2-l-adv-dataset.imageimage-classification10K<n<100K0 likes7.1k downloads26m agoHugging Face02Shanmuk4622 /E2AM_EfficientNetV2_S E2AM Ablation Results: EfficientNetV2-S Energy-aware training ablation study for EfficientNetV2-S across three image-classification datasets: CIFAR-10, CIFAR-100, and Tiny-ImageNet. Each dataset has 15 training variants (8 individual-method M0..M7, 7 cumulative ablation C0..C6) at 50 epochs, plus a 5-variant deployment pipeline (FP32 baseline, structured pruning, pruning+finetune, INT8 quantization, pruned+INT8). Status: 45 completed variants, 0 partial. Quick links… See the full description on the dataset page: https://huggingface.co/datasets/Shanmuk4622/E2AM_EfficientNetV2_S.imagen<1K0 likes176 downloads4mo agoHugging Face03Priyo-05 /efficientnet_b0_b7_comparison_4000_rowstabular1K<n<10K0 likes12 downloads5mo agoHugging Face

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