{"url":"/dataset/corn-seeds-dataset","name":"Corn Seeds Dataset","full_name":null,"description_markdown":"This dataset is the images of corn seeds considering the top and bottom view independently (two images for one corn seed: top and bottom). There are four classes of the corn seed (Broken-B, Discolored-D, Silkcut-S, and Pure-P) 17802 images are labeled by the experts at the AdTech Corp. and 26K images were unlabeled out of which 9k images were labeled using the Active Learning (BatchBALD)\r\n\r\nWe have created three different dataset: (1). Primary dataset: contains the 17802 images labeled by the experts. Top-view(8901) and Bottom-view(8901).\r\n\r\n(2). Dataset with fake images: We generated fake images using Conditional GAN (BigGAN) as follows: broken-2937, discolored-5823, pure-2937, silkcut-5823 instances and added them into the train set to balance the data set.\r\n\r\n(3). Balanced dataset: In this case of adding newly captured images labeled using the Batch Active Learning method, new 9000 labeled images are added into the primary dataset. This new dataset contains 26,802 images split into train and validation set 80: 20, respectively. Contains the 17802 images and the 9K images labeled by the Active Learning (BatchBALD).","description_withheld":null,"homepage":"https://naagar.github.io/cornseedsdataset/","introduced_date":"2021-08-15","introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Image Classification","url":"/task/image-classification","datasets_with_task":"/datasets/task/image-classification"},{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"Image Generation","url":"/task/image-generation","datasets_with_task":"/datasets/task/image-generation"},{"name":"2D Semantic Segmentation","url":"/task/2d-semantic-segmentation","datasets_with_task":"/datasets/task/2d-semantic-segmentation"},{"name":"Fine-Grained Image Classification","url":"/task/fine-grained-image-classification","datasets_with_task":"/datasets/task/fine-grained-image-classification"},{"name":"Image Classification with Label Noise","url":"/task/image-classification-with-label-noise","datasets_with_task":"/datasets/task/image-classification-with-label-noise"},{"name":"3D Object Reconstruction","url":"/task/3d-object-reconstruction","datasets_with_task":"/datasets/task/3d-object-reconstruction"},{"name":"3D Classification","url":"/task/3d-classification","datasets_with_task":"/datasets/task/3d-classification"},{"name":"Zero-Shot Image Classification","url":"/task/zero-shot-image-classification","datasets_with_task":"/datasets/task/zero-shot-image-classification"},{"name":"3D Object Recognition","url":"/task/3d-object-recognition","datasets_with_task":"/datasets/task/3d-object-recognition"},{"name":"Multi-Label Learning","url":"/task/multi-label-learning","datasets_with_task":"/datasets/task/multi-label-learning"},{"name":"Fake Image Detection","url":"/task/fake-image-detection","datasets_with_task":"/datasets/task/fake-image-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Corn Seeds Dataset"],"data_loaders":[],"num_papers_in_archive":0,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}