ConvNext
Datasets
All datasets matching “ConvNext”neuralatlas-attributions-convnext_tinydanbooru-convnext-embeddings3E2AM_ConvNeXtV2_CIFAR10DeLR-Cephalometric-ConvNeXtV2
DeLR – Dual-encoder Landmark Regression
A PyTorch implementation of the DeLR (Dual-encoder Landmark Regression) architecture for cephalometric landmark detection, evaluated on three public datasets:
Aariz Cephalograms — 1000 images, 29 annotated landmarks (700 / 150 / 150 train/valid/test).
CephAdoAdu Dataset — 700 images, 10 landmarks, mixed adolescent + adult cohort (400 train / 300 test in the official splits; we held out 10 % of train as validation).
ISBI 2015 Cephalometric… See the full description on the dataset page: https://huggingface.co/datasets/emad2001/DeLR-Cephalometric-ConvNeXtV2.E2AM_ConvNeXtV2Nano
E2AM Ablation Results: ConvNeXtV2-Nano
Energy-aware training ablation study for ConvNeXtV2-Nano 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. 15 deployment runs.… See the full description on the dataset page: https://huggingface.co/datasets/Shanmuk4622/E2AM_ConvNeXtV2Nano.E2AM_ConvNeXtV2Tiny
E2AM Ablation Results: ConvNeXtV2-Tiny
Energy-aware training ablation study for ConvNeXtV2-Tiny 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. 15 deployment runs.… See the full description on the dataset page: https://huggingface.co/datasets/Shanmuk4622/E2AM_ConvNeXtV2Tiny.