datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
neuralatlas-attributions-efficientnet_b0
Neural Atlas attributions — efficientnet_b0 on imagenet-pico
Precomputed attribution maps and faithfulness metrics for the torchvision
efficientnet_b0 model (default pretrained weights, no fine-tuning) on imagenet-pico,
a 3000-image subset of ImageNet-1k with three images for each of the 1000
classes.
This repository is part of Neural Atlas, a web tool for comparing
attribution methods across vision architectures on the same image, developed
as an undergraduate thesis at the… See the full description on the dataset page: https://huggingface.co/datasets/Matgc04/neuralatlas-attributions-efficientnet_b0.neuralatlas-attributions-efficientnet_b4
Neural Atlas attributions — efficientnet_b4 on imagenet-pico
Precomputed attribution maps and faithfulness metrics for the torchvision
efficientnet_b4 model (default pretrained weights, no fine-tuning) on imagenet-pico,
a 3000-image subset of ImageNet-1k with three images for each of the 1000
classes.
This repository is part of Neural Atlas, a web tool for comparing
attribution methods across vision architectures on the same image, developed
as an undergraduate thesis at the… See the full description on the dataset page: https://huggingface.co/datasets/Matgc04/neuralatlas-attributions-efficientnet_b4.EfficientMaize_classification
Efficientmaize Classification
A dataset for quality classification of maize. The dataset contains raw and augmented versions.The raw dataset contains 4,846 images.Images per class:
Bad: 2,211
Good: 2,635
The augmented dataset contains 28,899 images.Images per class:
Bad: 13,246
Good: 15,653
This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.
Citation
@article{asante2024efficientmaize,
title={EfficientMaize: A… See the full description on the dataset page: https://huggingface.co/datasets/Project-AgML/EfficientMaize_classification.