Corn Kernel Counting Dataset

Stream data with DDA:

from dagshub.streaming import DagsHubFilesystem

fs = DagsHubFilesystem(".", repo_url="https://dagshub.com/DagsHub-Datasets/intelinair_corn_kernel_counting-dataset")

fs.listdir("s3://intelinair-data-releases/corn-kernel-counting")

Description:

Dataset associated with the March 2021 Frontiers in Robotics and AI paper "Broad Dataset and Methods for Counting and Localization of On-Ear Corn Kernels", DOI: 10.3389/frobt.2021.627009

Contact:

Dataset associated with the March 2021 Frontiers in Robotics and AI paper "Broad Dataset and Methods for Counting and Localization of On-Ear Corn Kernels", DOI: 10.3389/frobt.2021.627009

Update Frequency:

Periodically

Managed By:

Intelinair, Inc.

Resources:

1. resource:

   • Description: Folder contains the terms of use, paper, and zip file of data in COOC format. Each kernel is annotated with an instance mask and appropriate class. The dataset is broken into three subcomponents. The "base" (i.e. "corn") subset contains images from a wide variety of domains such as those you might find on the internet. The "narrow" subset contains images with a single ear as would be anticipated in the application. The "many" dataset resembles the base dataset but has a huge number of ears and kernels in each image. Images were annotated for (healthy) kernels, diseased kernels, “incomplete” (i.e. not fully matured) kernels, barren tips (i.e where the top of the ear does not produce kernels), and “kernel areas” where on-ear kernels were166present but resolution/lighting prevented annotation.

   • ARN: arn:aws:s3:::intelinair-data-releases/corn-kernel-counting

   • Region: us-east-1

   • Type: S3 Bucket

   • RequesterPays: False

Tags:

agriculture, computer vision, machine learning

Publication:

1. publication:
   • Title: Broad Dataset and Methods for Counting and Localization of On-Ear Corn Kernels
   • URL: https://www.frontiersin.org/articles/10.3389/frobt.2021.627009/abstract
   • AuthorName: Jennifer Hobbs, Vachik Khachatryan, Barathwaj Anandan, Harutyun Hovhannisyan, David Wilson